Overview

Brought to you by YData

Dataset statistics

Number of variables66
Number of observations4733
Missing cells122112
Missing cells (%)39.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.4 MiB
Average record size in memory3.6 KiB

Variable types

Numeric15
URL13
Text12
Categorical14
DateTime4
Unsupported8

Alerts

_embedded_show_averageRuntime is highly overall correlated with _embedded_show_network_country_code and 6 other fieldsHigh correlation
_embedded_show_externals_thetvdb is highly overall correlated with _embedded_show_externals_tvrage and 9 other fieldsHigh correlation
_embedded_show_externals_tvrage is highly overall correlated with _embedded_show_externals_thetvdb and 13 other fieldsHigh correlation
_embedded_show_id is highly overall correlated with _embedded_show_externals_thetvdb and 6 other fieldsHigh correlation
_embedded_show_language is highly overall correlated with _embedded_show_externals_tvrage and 10 other fieldsHigh correlation
_embedded_show_network_country_code is highly overall correlated with _embedded_show_averageRuntime and 23 other fieldsHigh correlation
_embedded_show_network_country_name is highly overall correlated with _embedded_show_averageRuntime and 23 other fieldsHigh correlation
_embedded_show_network_country_timezone is highly overall correlated with _embedded_show_averageRuntime and 23 other fieldsHigh correlation
_embedded_show_network_id is highly overall correlated with _embedded_show_externals_tvrage and 13 other fieldsHigh correlation
_embedded_show_network_name is highly overall correlated with _embedded_show_averageRuntime and 25 other fieldsHigh correlation
_embedded_show_network_officialSite is highly overall correlated with _embedded_show_averageRuntime and 25 other fieldsHigh correlation
_embedded_show_rating_average is highly overall correlated with _embedded_show_network_country_code and 5 other fieldsHigh correlation
_embedded_show_runtime is highly overall correlated with _embedded_show_averageRuntime and 8 other fieldsHigh correlation
_embedded_show_schedule_time is highly overall correlated with _embedded_show_externals_thetvdb and 8 other fieldsHigh correlation
_embedded_show_status is highly overall correlated with _embedded_show_externals_tvrage and 10 other fieldsHigh correlation
_embedded_show_type is highly overall correlated with _embedded_show_externals_tvrage and 4 other fieldsHigh correlation
_embedded_show_updated is highly overall correlated with _embedded_show_network_country_code and 4 other fieldsHigh correlation
_embedded_show_webChannel_country_code is highly overall correlated with _embedded_show_externals_tvrage and 12 other fieldsHigh correlation
_embedded_show_webChannel_country_name is highly overall correlated with _embedded_show_externals_tvrage and 12 other fieldsHigh correlation
_embedded_show_webChannel_country_timezone is highly overall correlated with _embedded_show_externals_tvrage and 12 other fieldsHigh correlation
_embedded_show_webChannel_id is highly overall correlated with _embedded_show_network_country_code and 7 other fieldsHigh correlation
_embedded_show_weight is highly overall correlated with _embedded_show_externals_thetvdb and 6 other fieldsHigh correlation
id is highly overall correlated with _embedded_show_network_name and 1 other fieldsHigh correlation
number is highly overall correlated with _embedded_show_network_name and 3 other fieldsHigh correlation
rating_average is highly overall correlated with _embedded_show_network_country_code and 3 other fieldsHigh correlation
runtime is highly overall correlated with _embedded_show_averageRuntime and 7 other fieldsHigh correlation
season is highly overall correlated with _embedded_show_externals_thetvdb and 10 other fieldsHigh correlation
type is highly overall correlated with _embedded_show_network_country_code and 6 other fieldsHigh correlation
type is highly imbalanced (96.2%) Imbalance
_embedded_show_schedule_time is highly imbalanced (50.1%) Imbalance
airtime has 2428 (51.3%) missing values Missing
runtime has 444 (9.4%) missing values Missing
image has 4733 (100.0%) missing values Missing
summary has 3268 (69.0%) missing values Missing
rating_average has 4394 (92.8%) missing values Missing
_embedded_show_language has 310 (6.5%) missing values Missing
_embedded_show_runtime has 3533 (74.6%) missing values Missing
_embedded_show_averageRuntime has 300 (6.3%) missing values Missing
_embedded_show_ended has 3037 (64.2%) missing values Missing
_embedded_show_officialSite has 442 (9.3%) missing values Missing
_embedded_show_rating_average has 4022 (85.0%) missing values Missing
_embedded_show_network has 4733 (100.0%) missing values Missing
_embedded_show_webChannel_id has 112 (2.4%) missing values Missing
_embedded_show_webChannel_name has 112 (2.4%) missing values Missing
_embedded_show_webChannel_country_name has 1595 (33.7%) missing values Missing
_embedded_show_webChannel_country_code has 1595 (33.7%) missing values Missing
_embedded_show_webChannel_country_timezone has 1595 (33.7%) missing values Missing
_embedded_show_webChannel_officialSite has 1376 (29.1%) missing values Missing
_embedded_show_dvdCountry has 4733 (100.0%) missing values Missing
_embedded_show_externals_tvrage has 4555 (96.2%) missing values Missing
_embedded_show_externals_thetvdb has 1487 (31.4%) missing values Missing
_embedded_show_externals_imdb has 2599 (54.9%) missing values Missing
_embedded_show_image_medium has 249 (5.3%) missing values Missing
_embedded_show_image_original has 249 (5.3%) missing values Missing
_embedded_show_summary has 772 (16.3%) missing values Missing
_embedded_show_image has 4733 (100.0%) missing values Missing
_embedded_show__links_nextepisode_href has 4165 (88.0%) missing values Missing
_embedded_show__links_nextepisode_name has 4165 (88.0%) missing values Missing
image_medium has 3517 (74.3%) missing values Missing
image_original has 3517 (74.3%) missing values Missing
_embedded_show_network_id has 4217 (89.1%) missing values Missing
_embedded_show_network_name has 4217 (89.1%) missing values Missing
_embedded_show_network_country_name has 4217 (89.1%) missing values Missing
_embedded_show_network_country_code has 4217 (89.1%) missing values Missing
_embedded_show_network_country_timezone has 4217 (89.1%) missing values Missing
_embedded_show_network_officialSite has 4575 (96.7%) missing values Missing
_embedded_show_webChannel has 4733 (100.0%) missing values Missing
_embedded_show_webChannel_country has 4733 (100.0%) missing values Missing
_embedded_show_dvdCountry_name has 4729 (99.9%) missing values Missing
_embedded_show_dvdCountry_code has 4729 (99.9%) missing values Missing
_embedded_show_dvdCountry_timezone has 4729 (99.9%) missing values Missing
id has unique values Unique
url has unique values Unique
_links_self_href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded_show_genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded_show_schedule_days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded_show_network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded_show_dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded_show_image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded_show_webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded_show_webChannel_country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded_show_weight has 135 (2.9%) zeros Zeros

Reproduction

Analysis started2024-10-29 19:31:06.467578
Analysis finished2024-10-29 19:34:41.488391
Duration3 minutes and 35.02 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

id
Real number (ℝ)

High correlation  Unique 

Distinct4733
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2767629.8
Minimum2391730
Maximum3037097
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:41.564827image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum2391730
5-th percentile2693704.6
Q12732495
median2744331
Q32775823
95-th percentile2921731.4
Maximum3037097
Range645367
Interquartile range (IQR)43328

Descriptive statistics

Standard deviation69337.578
Coefficient of variation (CV)0.025053054
Kurtosis2.612156
Mean2767629.8
Median Absolute Deviation (MAD)14503
Skewness1.5647251
Sum1.3099192 × 1010
Variance4.8076997 × 109
MonotonicityNot monotonic
2024-10-29T14:34:41.693730image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2730586 1
 
< 0.1%
2743405 1
 
< 0.1%
2748583 1
 
< 0.1%
2748582 1
 
< 0.1%
2748581 1
 
< 0.1%
2748580 1
 
< 0.1%
2748579 1
 
< 0.1%
2735438 1
 
< 0.1%
2826704 1
 
< 0.1%
2756123 1
 
< 0.1%
Other values (4723) 4723
99.8%
ValueCountFrequency (%)
2391730 1
< 0.1%
2494160 1
< 0.1%
2580338 1
< 0.1%
2580339 1
< 0.1%
2610881 1
< 0.1%
2610882 1
< 0.1%
2625941 1
< 0.1%
2633274 1
< 0.1%
2633275 1
< 0.1%
2633276 1
< 0.1%
ValueCountFrequency (%)
3037097 1
< 0.1%
3034747 1
< 0.1%
3034745 1
< 0.1%
3032636 1
< 0.1%
3032635 1
< 0.1%
3030200 1
< 0.1%
3030199 1
< 0.1%
3030198 1
< 0.1%
3030197 1
< 0.1%
3030124 1
< 0.1%

url
URL

Unique 

Distinct4733
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size629.1 KiB
https://www.tvmaze.com/episodes/2730586/neznost-2x01-seria-1
 
1
https://www.tvmaze.com/episodes/2743405/alle-mot-alle-8x09-guttene-mot-jentene
 
1
https://www.tvmaze.com/episodes/2748583/not-quite-narwhal-2x06-the-artist
 
1
https://www.tvmaze.com/episodes/2748582/not-quite-narwhal-2x05-berry-race
 
1
https://www.tvmaze.com/episodes/2748581/not-quite-narwhal-2x04-theo
 
1
Other values (4728)
4728 
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2730586/neznost-2x01-seria-1 1
 
< 0.1%
https://www.tvmaze.com/episodes/2743405/alle-mot-alle-8x09-guttene-mot-jentene 1
 
< 0.1%
https://www.tvmaze.com/episodes/2748583/not-quite-narwhal-2x06-the-artist 1
 
< 0.1%
https://www.tvmaze.com/episodes/2748582/not-quite-narwhal-2x05-berry-race 1
 
< 0.1%
https://www.tvmaze.com/episodes/2748581/not-quite-narwhal-2x04-theo 1
 
< 0.1%
https://www.tvmaze.com/episodes/2748580/not-quite-narwhal-2x03-shark-and-pilot-fish 1
 
< 0.1%
https://www.tvmaze.com/episodes/2748579/not-quite-narwhal-2x02-the-white-whale 1
 
< 0.1%
https://www.tvmaze.com/episodes/2735438/not-quite-narwhal-2x01-best-friends-day 1
 
< 0.1%
https://www.tvmaze.com/episodes/2826704/snacked-7x02-wwe-superstars-bianca-belair-montez-ford-unleash-their-favorite-snack-combos 1
 
< 0.1%
https://www.tvmaze.com/episodes/2756123/kismetse-olur-askin-gucu-2x102-episode-102 1
 
< 0.1%
Other values (4723) 4723
99.8%
ValueCountFrequency (%)
https 4733
100.0%
ValueCountFrequency (%)
www.tvmaze.com 4733
100.0%
ValueCountFrequency (%)
/episodes/2730586/neznost-2x01-seria-1 1
 
< 0.1%
/episodes/2743405/alle-mot-alle-8x09-guttene-mot-jentene 1
 
< 0.1%
/episodes/2748583/not-quite-narwhal-2x06-the-artist 1
 
< 0.1%
/episodes/2748582/not-quite-narwhal-2x05-berry-race 1
 
< 0.1%
/episodes/2748581/not-quite-narwhal-2x04-theo 1
 
< 0.1%
/episodes/2748580/not-quite-narwhal-2x03-shark-and-pilot-fish 1
 
< 0.1%
/episodes/2748579/not-quite-narwhal-2x02-the-white-whale 1
 
< 0.1%
/episodes/2735438/not-quite-narwhal-2x01-best-friends-day 1
 
< 0.1%
/episodes/2826704/snacked-7x02-wwe-superstars-bianca-belair-montez-ford-unleash-their-favorite-snack-combos 1
 
< 0.1%
/episodes/2756123/kismetse-olur-askin-gucu-2x102-episode-102 1
 
< 0.1%
Other values (4723) 4723
99.8%
ValueCountFrequency (%)
4733
100.0%
ValueCountFrequency (%)
4733
100.0%

name
Text

Distinct2346
Distinct (%)49.6%
Missing0
Missing (%)0.0%
Memory size373.1 KiB
2024-10-29T14:34:42.025502image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length129
Median length121
Mean length14.983097
Min length2

Characters and Unicode

Total characters70915
Distinct characters436
Distinct categories13 ?
Distinct scripts7 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2157 ?
Unique (%)45.6%

Sample

1st rowСерия 1
2nd rowСерия 2
3rd rowСерия 3
4th rowСерия 4
5th rowСерия 5
ValueCountFrequency (%)
episode 2443
 
18.3%
the 382
 
2.9%
1 190
 
1.4%
2 189
 
1.4%
серия 180
 
1.3%
3 156
 
1.2%
4 147
 
1.1%
141
 
1.1%
5 134
 
1.0%
6 128
 
1.0%
Other values (4313) 9283
69.4%
2024-10-29T14:34:42.520159image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8648
 
12.2%
e 5825
 
8.2%
o 4550
 
6.4%
i 4389
 
6.2%
s 4071
 
5.7%
d 3382
 
4.8%
p 2913
 
4.1%
E 2761
 
3.9%
a 2552
 
3.6%
n 2124
 
3.0%
Other values (426) 29700
41.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 45153
63.7%
Uppercase Letter 9296
 
13.1%
Space Separator 8648
 
12.2%
Decimal Number 5862
 
8.3%
Other Punctuation 1084
 
1.5%
Other Letter 554
 
0.8%
Dash Punctuation 141
 
0.2%
Math Symbol 59
 
0.1%
Close Punctuation 45
 
0.1%
Open Punctuation 45
 
0.1%
Other values (3) 28
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ل 54
 
9.7%
ا 31
 
5.6%
ح 26
 
4.7%
25
 
4.5%
ق 24
 
4.3%
ة 23
 
4.2%
18
 
3.2%
10
 
1.8%
10
 
1.8%
10
 
1.8%
Other values (166) 323
58.3%
Lowercase Letter
ValueCountFrequency (%)
e 5825
12.9%
o 4550
 
10.1%
i 4389
 
9.7%
s 4071
 
9.0%
d 3382
 
7.5%
p 2913
 
6.5%
a 2552
 
5.7%
n 2124
 
4.7%
r 1825
 
4.0%
t 1800
 
4.0%
Other values (129) 11722
26.0%
Uppercase Letter
ValueCountFrequency (%)
E 2761
29.7%
T 602
 
6.5%
S 484
 
5.2%
A 402
 
4.3%
B 369
 
4.0%
C 322
 
3.5%
F 315
 
3.4%
D 292
 
3.1%
P 289
 
3.1%
M 287
 
3.1%
Other values (71) 3173
34.1%
Other Punctuation
ValueCountFrequency (%)
, 265
24.4%
. 195
18.0%
' 152
14.0%
: 132
12.2%
? 86
 
7.9%
/ 73
 
6.7%
! 70
 
6.5%
# 56
 
5.2%
" 32
 
3.0%
& 15
 
1.4%
Other values (4) 8
 
0.7%
Decimal Number
ValueCountFrequency (%)
1 1433
24.4%
2 1027
17.5%
3 561
 
9.6%
4 554
 
9.5%
0 481
 
8.2%
5 385
 
6.6%
6 381
 
6.5%
8 360
 
6.1%
7 351
 
6.0%
9 329
 
5.6%
Math Symbol
ValueCountFrequency (%)
| 43
72.9%
~ 12
 
20.3%
+ 3
 
5.1%
× 1
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
- 131
92.9%
6
 
4.3%
4
 
2.8%
Close Punctuation
ValueCountFrequency (%)
) 43
95.6%
] 2
 
4.4%
Open Punctuation
ValueCountFrequency (%)
( 43
95.6%
[ 2
 
4.4%
Final Punctuation
ValueCountFrequency (%)
» 10
58.8%
7
41.2%
Space Separator
ValueCountFrequency (%)
8648
100.0%
Initial Punctuation
ValueCountFrequency (%)
« 10
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 49445
69.7%
Common 15912
 
22.4%
Cyrillic 4819
 
6.8%
Hangul 353
 
0.5%
Arabic 201
 
0.3%
Armenian 148
 
0.2%
Greek 37
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
25
 
7.1%
18
 
5.1%
10
 
2.8%
10
 
2.8%
10
 
2.8%
7
 
2.0%
7
 
2.0%
6
 
1.7%
6
 
1.7%
6
 
1.7%
Other values (141) 248
70.3%
Latin
ValueCountFrequency (%)
e 5825
 
11.8%
o 4550
 
9.2%
i 4389
 
8.9%
s 4071
 
8.2%
d 3382
 
6.8%
p 2913
 
5.9%
E 2761
 
5.6%
a 2552
 
5.2%
n 2124
 
4.3%
r 1825
 
3.7%
Other values (90) 15053
30.4%
Cyrillic
ValueCountFrequency (%)
е 424
 
8.8%
р 416
 
8.6%
и 411
 
8.5%
а 355
 
7.4%
о 308
 
6.4%
я 250
 
5.2%
С 232
 
4.8%
н 210
 
4.4%
к 170
 
3.5%
т 156
 
3.2%
Other values (57) 1887
39.2%
Common
ValueCountFrequency (%)
8648
54.3%
1 1433
 
9.0%
2 1027
 
6.5%
3 561
 
3.5%
4 554
 
3.5%
0 481
 
3.0%
5 385
 
2.4%
6 381
 
2.4%
8 360
 
2.3%
7 351
 
2.2%
Other values (30) 1731
 
10.9%
Armenian
ValueCountFrequency (%)
ա 23
15.5%
ո 15
 
10.1%
ն 13
 
8.8%
ր 12
 
8.1%
ւ 9
 
6.1%
կ 8
 
5.4%
ե 8
 
5.4%
մ 6
 
4.1%
ի 5
 
3.4%
ղ 4
 
2.7%
Other values (23) 45
30.4%
Arabic
ValueCountFrequency (%)
ل 54
26.9%
ا 31
15.4%
ح 26
12.9%
ق 24
11.9%
ة 23
11.4%
ي 7
 
3.5%
و 4
 
2.0%
ن 4
 
2.0%
ب 4
 
2.0%
أ 3
 
1.5%
Other values (15) 21
 
10.4%
Greek
ValueCountFrequency (%)
υ 5
13.5%
ο 5
13.5%
λ 3
 
8.1%
α 3
 
8.1%
σ 3
 
8.1%
μ 2
 
5.4%
ι 2
 
5.4%
τ 2
 
5.4%
ό 1
 
2.7%
ή 1
 
2.7%
Other values (10) 10
27.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65009
91.7%
Cyrillic 4819
 
6.8%
None 361
 
0.5%
Hangul 353
 
0.5%
Arabic 203
 
0.3%
Armenian 148
 
0.2%
Punctuation 22
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8648
 
13.3%
e 5825
 
9.0%
o 4550
 
7.0%
i 4389
 
6.8%
s 4071
 
6.3%
d 3382
 
5.2%
p 2913
 
4.5%
E 2761
 
4.2%
a 2552
 
3.9%
n 2124
 
3.3%
Other values (72) 23794
36.6%
Cyrillic
ValueCountFrequency (%)
е 424
 
8.8%
р 416
 
8.6%
и 411
 
8.5%
а 355
 
7.4%
о 308
 
6.4%
я 250
 
5.2%
С 232
 
4.8%
н 210
 
4.4%
к 170
 
3.5%
т 156
 
3.2%
Other values (57) 1887
39.2%
Arabic
ValueCountFrequency (%)
ل 54
26.6%
ا 31
15.3%
ح 26
12.8%
ق 24
11.8%
ة 23
11.3%
ي 7
 
3.4%
و 4
 
2.0%
ن 4
 
2.0%
ب 4
 
2.0%
أ 3
 
1.5%
Other values (16) 23
11.3%
None
ValueCountFrequency (%)
ö 42
 
11.6%
ó 35
 
9.7%
ü 35
 
9.7%
é 28
 
7.8%
å 23
 
6.4%
ø 22
 
6.1%
á 21
 
5.8%
ä 18
 
5.0%
» 10
 
2.8%
« 10
 
2.8%
Other values (62) 117
32.4%
Hangul
ValueCountFrequency (%)
25
 
7.1%
18
 
5.1%
10
 
2.8%
10
 
2.8%
10
 
2.8%
7
 
2.0%
7
 
2.0%
6
 
1.7%
6
 
1.7%
6
 
1.7%
Other values (141) 248
70.3%
Armenian
ValueCountFrequency (%)
ա 23
15.5%
ո 15
 
10.1%
ն 13
 
8.8%
ր 12
 
8.1%
ւ 9
 
6.1%
կ 8
 
5.4%
ե 8
 
5.4%
մ 6
 
4.1%
ի 5
 
3.4%
ղ 4
 
2.7%
Other values (23) 45
30.4%
Punctuation
ValueCountFrequency (%)
7
31.8%
6
27.3%
4
18.2%
4
18.2%
1
 
4.5%

season
Real number (ℝ)

High correlation 

Distinct34
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean301.31206
Minimum1
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:42.644702image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q36
95-th percentile2024
Maximum2024
Range2023
Interquartile range (IQR)5

Descriptive statistics

Standard deviation716.58869
Coefficient of variation (CV)2.3782277
Kurtosis1.95659
Mean301.31206
Median Absolute Deviation (MAD)0
Skewness1.9887936
Sum1426110
Variance513499.35
MonotonicityNot monotonic
2024-10-29T14:34:42.771286image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 2500
52.8%
2024 694
 
14.7%
2 547
 
11.6%
3 259
 
5.5%
4 112
 
2.4%
5 104
 
2.2%
6 73
 
1.5%
8 65
 
1.4%
25 36
 
0.8%
11 33
 
0.7%
Other values (24) 310
 
6.5%
ValueCountFrequency (%)
1 2500
52.8%
2 547
 
11.6%
3 259
 
5.5%
4 112
 
2.4%
5 104
 
2.2%
6 73
 
1.5%
7 25
 
0.5%
8 65
 
1.4%
9 27
 
0.6%
10 26
 
0.5%
ValueCountFrequency (%)
2024 694
14.7%
2023 4
 
0.1%
54 4
 
0.1%
50 3
 
0.1%
41 8
 
0.2%
39 19
 
0.4%
34 4
 
0.1%
31 5
 
0.1%
30 20
 
0.4%
27 6
 
0.1%

number
Real number (ℝ)

High correlation 

Distinct183
Distinct (%)3.9%
Missing29
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean19.133503
Minimum1
Maximum959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:42.903676image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8
Q318
95-th percentile67
Maximum959
Range958
Interquartile range (IQR)14

Descriptive statistics

Standard deviation47.937016
Coefficient of variation (CV)2.5053967
Kurtosis174.05576
Mean19.133503
Median Absolute Deviation (MAD)6
Skewness11.026564
Sum90004
Variance2297.9575
MonotonicityNot monotonic
2024-10-29T14:34:43.044766image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 395
 
8.3%
2 369
 
7.8%
3 349
 
7.4%
4 310
 
6.5%
5 273
 
5.8%
6 255
 
5.4%
7 214
 
4.5%
8 203
 
4.3%
9 156
 
3.3%
10 145
 
3.1%
Other values (173) 2035
43.0%
ValueCountFrequency (%)
1 395
8.3%
2 369
7.8%
3 349
7.4%
4 310
6.5%
5 273
5.8%
6 255
5.4%
7 214
4.5%
8 203
4.3%
9 156
 
3.3%
10 145
 
3.1%
ValueCountFrequency (%)
959 1
< 0.1%
958 1
< 0.1%
957 1
< 0.1%
956 1
< 0.1%
955 1
< 0.1%
407 1
< 0.1%
406 1
< 0.1%
405 1
< 0.1%
404 1
< 0.1%
403 1
< 0.1%

type
Categorical

High correlation  Imbalance 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size296.3 KiB
regular
4704 
significant_special
 
18
insignificant_special
 
11

Length

Max length21
Median length7
Mean length7.0781745
Min length7

Characters and Unicode

Total characters33501
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular 4704
99.4%
significant_special 18
 
0.4%
insignificant_special 11
 
0.2%

Length

2024-10-29T14:34:43.171225image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T14:34:43.269017image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
regular 4704
99.4%
significant_special 18
 
0.4%
insignificant_special 11
 
0.2%

Most occurring characters

ValueCountFrequency (%)
r 9408
28.1%
a 4762
14.2%
e 4733
14.1%
g 4733
14.1%
l 4733
14.1%
u 4704
14.0%
i 127
 
0.4%
n 69
 
0.2%
s 58
 
0.2%
c 58
 
0.2%
Other values (4) 116
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 33472
99.9%
Connector Punctuation 29
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 9408
28.1%
a 4762
14.2%
e 4733
14.1%
g 4733
14.1%
l 4733
14.1%
u 4704
14.1%
i 127
 
0.4%
n 69
 
0.2%
s 58
 
0.2%
c 58
 
0.2%
Other values (3) 87
 
0.3%
Connector Punctuation
ValueCountFrequency (%)
_ 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 33472
99.9%
Common 29
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 9408
28.1%
a 4762
14.2%
e 4733
14.1%
g 4733
14.1%
l 4733
14.1%
u 4704
14.1%
i 127
 
0.4%
n 69
 
0.2%
s 58
 
0.2%
c 58
 
0.2%
Other values (3) 87
 
0.3%
Common
ValueCountFrequency (%)
_ 29
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33501
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 9408
28.1%
a 4762
14.2%
e 4733
14.1%
g 4733
14.1%
l 4733
14.1%
u 4704
14.0%
i 127
 
0.4%
n 69
 
0.2%
s 58
 
0.2%
c 58
 
0.2%
Other values (4) 116
 
0.3%

airdate
Categorical

Distinct31
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size309.8 KiB
2024-01-26
 
301
2024-01-19
 
265
2024-01-11
 
230
2024-01-18
 
217
2024-01-25
 
214
Other values (26)
3506 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters47330
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-01
2nd row2024-01-01
3rd row2024-01-01
4th row2024-01-01
5th row2024-01-01

Common Values

ValueCountFrequency (%)
2024-01-26 301
 
6.4%
2024-01-19 265
 
5.6%
2024-01-11 230
 
4.9%
2024-01-18 217
 
4.6%
2024-01-25 214
 
4.5%
2024-01-08 210
 
4.4%
2024-01-22 190
 
4.0%
2024-01-01 188
 
4.0%
2024-01-24 179
 
3.8%
2024-01-04 173
 
3.7%
Other values (21) 2566
54.2%

Length

2024-10-29T14:34:43.465997image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2024-01-26 301
 
6.4%
2024-01-19 265
 
5.6%
2024-01-11 230
 
4.9%
2024-01-18 217
 
4.6%
2024-01-25 214
 
4.5%
2024-01-08 210
 
4.4%
2024-01-22 190
 
4.0%
2024-01-01 188
 
4.0%
2024-01-24 179
 
3.8%
2024-01-04 173
 
3.7%
Other values (21) 2566
54.2%

Most occurring characters

ValueCountFrequency (%)
2 11505
24.3%
0 11103
23.5%
- 9466
20.0%
1 7058
14.9%
4 5164
10.9%
3 634
 
1.3%
9 548
 
1.2%
5 526
 
1.1%
8 515
 
1.1%
6 485
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37864
80.0%
Dash Punctuation 9466
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11505
30.4%
0 11103
29.3%
1 7058
18.6%
4 5164
13.6%
3 634
 
1.7%
9 548
 
1.4%
5 526
 
1.4%
8 515
 
1.4%
6 485
 
1.3%
7 326
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 9466
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47330
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11505
24.3%
0 11103
23.5%
- 9466
20.0%
1 7058
14.9%
4 5164
10.9%
3 634
 
1.3%
9 548
 
1.2%
5 526
 
1.1%
8 515
 
1.1%
6 485
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47330
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11505
24.3%
0 11103
23.5%
- 9466
20.0%
1 7058
14.9%
4 5164
10.9%
3 634
 
1.3%
9 548
 
1.2%
5 526
 
1.1%
8 515
 
1.1%
6 485
 
1.0%

airtime
Date

Missing 

Distinct65
Distinct (%)2.8%
Missing2428
Missing (%)51.3%
Memory size37.1 KiB
Minimum2024-10-29 00:00:00
Maximum2024-10-29 23:35:00
2024-10-29T14:34:43.581044image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:43.705989image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct855
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
Minimum2024-01-01 00:00:00+00:00
Maximum2024-02-01 04:35:00+00:00
2024-10-29T14:34:43.832183image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:43.968740image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

runtime
Real number (ℝ)

High correlation  Missing 

Distinct108
Distinct (%)2.5%
Missing444
Missing (%)9.4%
Infinite0
Infinite (%)0.0%
Mean44.401026
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:44.092764image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q118
median40
Q350
95-th percentile120
Maximum300
Range299
Interquartile range (IQR)32

Descriptive statistics

Standard deviation43.702726
Coefficient of variation (CV)0.98427288
Kurtosis11.713729
Mean44.401026
Median Absolute Deviation (MAD)17
Skewness3.0693289
Sum190436
Variance1909.9282
MonotonicityNot monotonic
2024-10-29T14:34:44.215174image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45 578
 
12.2%
15 314
 
6.6%
60 304
 
6.4%
30 205
 
4.3%
10 181
 
3.8%
120 142
 
3.0%
40 116
 
2.5%
3 116
 
2.5%
12 116
 
2.5%
43 114
 
2.4%
Other values (98) 2103
44.4%
(Missing) 444
 
9.4%
ValueCountFrequency (%)
1 7
 
0.1%
2 43
 
0.9%
3 116
2.5%
4 4
 
0.1%
5 41
 
0.9%
6 17
 
0.4%
7 39
 
0.8%
8 47
 
1.0%
9 17
 
0.4%
10 181
3.8%
ValueCountFrequency (%)
300 23
 
0.5%
240 71
1.5%
210 3
 
0.1%
205 1
 
< 0.1%
180 35
0.7%
173 1
 
< 0.1%
159 27
 
0.6%
150 3
 
0.1%
149 1
 
< 0.1%
142 2
 
< 0.1%

image
Unsupported

Missing  Rejected  Unsupported 

Missing4733
Missing (%)100.0%
Memory size37.1 KiB

summary
Text

Missing 

Distinct1459
Distinct (%)99.6%
Missing3268
Missing (%)69.0%
Memory size576.6 KiB
2024-10-29T14:34:44.542733image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length2299
Median length455
Mean length208.85939
Min length27

Characters and Unicode

Total characters305979
Distinct characters163
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1453 ?
Unique (%)99.2%

Sample

1st row<p>Lovers Alyona and Zakhar are preparing for the wedding, but she is tormented by doubts. The groom arranges a bachelor party for friends Igor, Yura and Max.</p>
2nd row<p>Friends are looking for the missing Zakhar, who was abandoned by Alyona. Zakhar wakes up in a hotel room with Alphonse Zhenya.</p>
3rd row<p>Lulin's astrawave powers arrive with a bang, blowing up her team's science project, and her friend, Spider, gets eaten by a giant alien plant!</p><p> </p><p><br /> </p>
4th row<p>Lulin misuses her new powers to speed everything up on Astoradian New Year's Day.</p>
5th row<p>A scavenger hunt turns into a monster hunt when Lulin starts to slime and is mistaken for the fabled Boggy Beast!</p>
ValueCountFrequency (%)
the 2665
 
5.3%
and 1704
 
3.4%
a 1684
 
3.3%
to 1657
 
3.3%
of 967
 
1.9%
in 800
 
1.6%
with 552
 
1.1%
is 552
 
1.1%
for 467
 
0.9%
his 447
 
0.9%
Other values (11258) 38786
77.1%
2024-10-29T14:34:45.001801image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48663
15.9%
e 27990
 
9.1%
a 19835
 
6.5%
t 19357
 
6.3%
i 16949
 
5.5%
n 16925
 
5.5%
o 16376
 
5.4%
s 16178
 
5.3%
r 14550
 
4.8%
h 11676
 
3.8%
Other values (153) 97480
31.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 230567
75.4%
Space Separator 48824
 
16.0%
Uppercase Letter 10269
 
3.4%
Other Punctuation 8497
 
2.8%
Math Symbol 6615
 
2.2%
Dash Punctuation 615
 
0.2%
Decimal Number 464
 
0.2%
Open Punctuation 54
 
< 0.1%
Close Punctuation 54
 
< 0.1%
Currency Symbol 9
 
< 0.1%
Other values (4) 11
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 27990
12.1%
a 19835
 
8.6%
t 19357
 
8.4%
i 16949
 
7.4%
n 16925
 
7.3%
o 16376
 
7.1%
s 16178
 
7.0%
r 14550
 
6.3%
h 11676
 
5.1%
l 9204
 
4.0%
Other values (67) 61527
26.7%
Uppercase Letter
ValueCountFrequency (%)
A 965
 
9.4%
T 957
 
9.3%
S 799
 
7.8%
M 649
 
6.3%
C 601
 
5.9%
B 535
 
5.2%
J 523
 
5.1%
D 494
 
4.8%
H 407
 
4.0%
P 397
 
3.9%
Other values (36) 3942
38.4%
Other Punctuation
ValueCountFrequency (%)
. 2843
33.5%
, 2275
26.8%
/ 1664
19.6%
' 1009
 
11.9%
" 174
 
2.0%
; 153
 
1.8%
? 146
 
1.7%
! 135
 
1.6%
: 65
 
0.8%
12
 
0.1%
Other values (3) 21
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 105
22.6%
1 91
19.6%
2 75
16.2%
4 44
9.5%
9 41
 
8.8%
3 30
 
6.5%
6 21
 
4.5%
5 20
 
4.3%
7 20
 
4.3%
8 17
 
3.7%
Math Symbol
ValueCountFrequency (%)
> 3306
50.0%
< 3306
50.0%
+ 3
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 543
88.3%
49
 
8.0%
23
 
3.7%
Space Separator
ValueCountFrequency (%)
48663
99.7%
  161
 
0.3%
Initial Punctuation
ValueCountFrequency (%)
6
75.0%
« 2
 
25.0%
Currency Symbol
ValueCountFrequency (%)
$ 6
66.7%
£ 3
33.3%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
» 1
100.0%
Other Symbol
ValueCountFrequency (%)
® 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 238472
77.9%
Common 65143
 
21.3%
Cyrillic 2364
 
0.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 27990
11.7%
a 19835
 
8.3%
t 19357
 
8.1%
i 16949
 
7.1%
n 16925
 
7.1%
o 16376
 
6.9%
s 16178
 
6.8%
r 14550
 
6.1%
h 11676
 
4.9%
l 9204
 
3.9%
Other values (60) 69432
29.1%
Cyrillic
ValueCountFrequency (%)
о 217
 
9.2%
а 189
 
8.0%
е 187
 
7.9%
и 169
 
7.1%
н 150
 
6.3%
т 149
 
6.3%
с 118
 
5.0%
р 107
 
4.5%
л 104
 
4.4%
в 99
 
4.2%
Other values (43) 875
37.0%
Common
ValueCountFrequency (%)
48663
74.7%
> 3306
 
5.1%
< 3306
 
5.1%
. 2843
 
4.4%
, 2275
 
3.5%
/ 1664
 
2.6%
' 1009
 
1.5%
- 543
 
0.8%
" 174
 
0.3%
  161
 
0.2%
Other values (30) 1199
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 303281
99.1%
Cyrillic 2364
 
0.8%
None 244
 
0.1%
Punctuation 90
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48663
16.0%
e 27990
 
9.2%
a 19835
 
6.5%
t 19357
 
6.4%
i 16949
 
5.6%
n 16925
 
5.6%
o 16376
 
5.4%
s 16178
 
5.3%
r 14550
 
4.8%
h 11676
 
3.8%
Other values (73) 94782
31.3%
Cyrillic
ValueCountFrequency (%)
о 217
 
9.2%
а 189
 
8.0%
е 187
 
7.9%
и 169
 
7.1%
н 150
 
6.3%
т 149
 
6.3%
с 118
 
5.0%
р 107
 
4.5%
л 104
 
4.4%
в 99
 
4.2%
Other values (43) 875
37.0%
None
ValueCountFrequency (%)
  161
66.0%
é 17
 
7.0%
ö 11
 
4.5%
å 8
 
3.3%
í 6
 
2.5%
ó 6
 
2.5%
ü 5
 
2.0%
ø 4
 
1.6%
æ 3
 
1.2%
£ 3
 
1.2%
Other values (13) 20
 
8.2%
Punctuation
ValueCountFrequency (%)
49
54.4%
23
25.6%
12
 
13.3%
6
 
6.7%

rating_average
Real number (ℝ)

High correlation  Missing 

Distinct43
Distinct (%)12.7%
Missing4394
Missing (%)92.8%
Infinite0
Infinite (%)0.0%
Mean7.4882006
Minimum3
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:45.136150image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile5.5
Q16.8
median7.5
Q38.4
95-th percentile9.02
Maximum10
Range7
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.2211557
Coefficient of variation (CV)0.16307733
Kurtosis2.0030265
Mean7.4882006
Median Absolute Deviation (MAD)0.8
Skewness-0.90456214
Sum2538.5
Variance1.4912213
MonotonicityNot monotonic
2024-10-29T14:34:45.270796image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
9 32
 
0.7%
7 27
 
0.6%
7.3 24
 
0.5%
7.5 20
 
0.4%
8.5 18
 
0.4%
6.5 16
 
0.3%
7.8 16
 
0.3%
6.7 15
 
0.3%
8 15
 
0.3%
6 13
 
0.3%
Other values (33) 143
 
3.0%
(Missing) 4394
92.8%
ValueCountFrequency (%)
3 3
 
0.1%
3.5 4
 
0.1%
4 4
 
0.1%
4.5 1
 
< 0.1%
5 1
 
< 0.1%
5.4 1
 
< 0.1%
5.5 5
 
0.1%
5.7 1
 
< 0.1%
6 13
0.3%
6.2 1
 
< 0.1%
ValueCountFrequency (%)
10 4
 
0.1%
9.7 1
 
< 0.1%
9.5 3
 
0.1%
9.4 3
 
0.1%
9.3 2
 
< 0.1%
9.2 4
 
0.1%
9 32
0.7%
8.9 1
 
< 0.1%
8.8 4
 
0.1%
8.7 11
 
0.2%

_links_self_href
URL

Unique 

Distinct4733
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size443.8 KiB
https://api.tvmaze.com/episodes/2730586
 
1
https://api.tvmaze.com/episodes/2743405
 
1
https://api.tvmaze.com/episodes/2748583
 
1
https://api.tvmaze.com/episodes/2748582
 
1
https://api.tvmaze.com/episodes/2748581
 
1
Other values (4728)
4728 
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/2730586 1
 
< 0.1%
https://api.tvmaze.com/episodes/2743405 1
 
< 0.1%
https://api.tvmaze.com/episodes/2748583 1
 
< 0.1%
https://api.tvmaze.com/episodes/2748582 1
 
< 0.1%
https://api.tvmaze.com/episodes/2748581 1
 
< 0.1%
https://api.tvmaze.com/episodes/2748580 1
 
< 0.1%
https://api.tvmaze.com/episodes/2748579 1
 
< 0.1%
https://api.tvmaze.com/episodes/2735438 1
 
< 0.1%
https://api.tvmaze.com/episodes/2826704 1
 
< 0.1%
https://api.tvmaze.com/episodes/2756123 1
 
< 0.1%
Other values (4723) 4723
99.8%
ValueCountFrequency (%)
https 4733
100.0%
ValueCountFrequency (%)
api.tvmaze.com 4733
100.0%
ValueCountFrequency (%)
/episodes/2730586 1
 
< 0.1%
/episodes/2743405 1
 
< 0.1%
/episodes/2748583 1
 
< 0.1%
/episodes/2748582 1
 
< 0.1%
/episodes/2748581 1
 
< 0.1%
/episodes/2748580 1
 
< 0.1%
/episodes/2748579 1
 
< 0.1%
/episodes/2735438 1
 
< 0.1%
/episodes/2826704 1
 
< 0.1%
/episodes/2756123 1
 
< 0.1%
Other values (4723) 4723
99.8%
ValueCountFrequency (%)
4733
100.0%
ValueCountFrequency (%)
4733
100.0%
Distinct681
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size420.4 KiB
https://api.tvmaze.com/shows/78854
 
100
https://api.tvmaze.com/shows/73952
 
38
https://api.tvmaze.com/shows/73773
 
36
https://api.tvmaze.com/shows/72654
 
36
https://api.tvmaze.com/shows/73703
 
36
Other values (676)
4487 
ValueCountFrequency (%)
https://api.tvmaze.com/shows/78854 100
 
2.1%
https://api.tvmaze.com/shows/73952 38
 
0.8%
https://api.tvmaze.com/shows/73773 36
 
0.8%
https://api.tvmaze.com/shows/72654 36
 
0.8%
https://api.tvmaze.com/shows/73703 36
 
0.8%
https://api.tvmaze.com/shows/74045 34
 
0.7%
https://api.tvmaze.com/shows/42056 33
 
0.7%
https://api.tvmaze.com/shows/69806 32
 
0.7%
https://api.tvmaze.com/shows/73931 30
 
0.6%
https://api.tvmaze.com/shows/74100 28
 
0.6%
Other values (671) 4330
91.5%
ValueCountFrequency (%)
https 4733
100.0%
ValueCountFrequency (%)
api.tvmaze.com 4733
100.0%
ValueCountFrequency (%)
/shows/78854 100
 
2.1%
/shows/73952 38
 
0.8%
/shows/73773 36
 
0.8%
/shows/72654 36
 
0.8%
/shows/73703 36
 
0.8%
/shows/74045 34
 
0.7%
/shows/42056 33
 
0.7%
/shows/69806 32
 
0.7%
/shows/73931 30
 
0.6%
/shows/74100 28
 
0.6%
Other values (671) 4330
91.5%
ValueCountFrequency (%)
4733
100.0%
ValueCountFrequency (%)
4733
100.0%
Distinct679
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size375.2 KiB
2024-10-29T14:34:45.630415image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length63
Median length41
Mean length17.485527
Min length2

Characters and Unicode

Total characters82759
Distinct characters167
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)1.8%

Sample

1st rowНежность
2nd rowНежность
3rd rowНежность
4th rowНежность
5th rowНежность
ValueCountFrequency (%)
the 777
 
5.2%
of 340
 
2.3%
my 226
 
1.5%
love 179
 
1.2%
news 171
 
1.2%
a 169
 
1.1%
and 160
 
1.1%
with 130
 
0.9%
you 122
 
0.8%
world 108
 
0.7%
Other values (1394) 12453
83.9%
2024-10-29T14:34:46.103925image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10102
 
12.2%
e 7415
 
9.0%
a 5003
 
6.0%
o 4569
 
5.5%
i 4287
 
5.2%
n 4222
 
5.1%
r 3861
 
4.7%
t 3378
 
4.1%
s 3153
 
3.8%
l 2473
 
3.0%
Other values (157) 34296
41.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 57480
69.5%
Uppercase Letter 13889
 
16.8%
Space Separator 10102
 
12.2%
Other Punctuation 808
 
1.0%
Decimal Number 338
 
0.4%
Dash Punctuation 112
 
0.1%
Math Symbol 19
 
< 0.1%
Other Symbol 11
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 7415
12.9%
a 5003
 
8.7%
o 4569
 
7.9%
i 4287
 
7.5%
n 4222
 
7.3%
r 3861
 
6.7%
t 3378
 
5.9%
s 3153
 
5.5%
l 2473
 
4.3%
h 2308
 
4.0%
Other values (72) 16811
29.2%
Uppercase Letter
ValueCountFrequency (%)
S 1227
 
8.8%
T 1170
 
8.4%
M 884
 
6.4%
L 845
 
6.1%
B 781
 
5.6%
A 762
 
5.5%
D 675
 
4.9%
C 673
 
4.8%
W 665
 
4.8%
H 621
 
4.5%
Other values (48) 5586
40.2%
Other Punctuation
ValueCountFrequency (%)
: 296
36.6%
' 274
33.9%
& 58
 
7.2%
! 44
 
5.4%
. 37
 
4.6%
, 30
 
3.7%
/ 23
 
2.8%
@ 22
 
2.7%
? 18
 
2.2%
* 3
 
0.4%
Decimal Number
ValueCountFrequency (%)
4 65
19.2%
1 63
18.6%
3 48
14.2%
2 48
14.2%
0 35
10.4%
7 32
9.5%
9 30
8.9%
8 8
 
2.4%
5 5
 
1.5%
6 4
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 100
89.3%
12
 
10.7%
Other Symbol
ValueCountFrequency (%)
° 7
63.6%
4
36.4%
Space Separator
ValueCountFrequency (%)
10102
100.0%
Math Symbol
ValueCountFrequency (%)
+ 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 67679
81.8%
Common 11390
 
13.8%
Cyrillic 3676
 
4.4%
Greek 14
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 7415
 
11.0%
a 5003
 
7.4%
o 4569
 
6.8%
i 4287
 
6.3%
n 4222
 
6.2%
r 3861
 
5.7%
t 3378
 
5.0%
s 3153
 
4.7%
l 2473
 
3.7%
h 2308
 
3.4%
Other values (66) 27010
39.9%
Cyrillic
ValueCountFrequency (%)
о 307
 
8.4%
е 302
 
8.2%
а 288
 
7.8%
и 244
 
6.6%
р 222
 
6.0%
н 212
 
5.8%
с 172
 
4.7%
т 171
 
4.7%
д 140
 
3.8%
я 139
 
3.8%
Other values (47) 1479
40.2%
Common
ValueCountFrequency (%)
10102
88.7%
: 296
 
2.6%
' 274
 
2.4%
- 100
 
0.9%
4 65
 
0.6%
1 63
 
0.6%
& 58
 
0.5%
3 48
 
0.4%
2 48
 
0.4%
! 44
 
0.4%
Other values (17) 292
 
2.6%
Greek
ValueCountFrequency (%)
ς 2
14.3%
Κ 2
14.3%
έ 2
14.3%
τ 2
14.3%
σ 2
14.3%
ω 2
14.3%
λ 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78676
95.1%
Cyrillic 3676
 
4.4%
None 388
 
0.5%
Punctuation 15
 
< 0.1%
Geometric Shapes 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10102
 
12.8%
e 7415
 
9.4%
a 5003
 
6.4%
o 4569
 
5.8%
i 4287
 
5.4%
n 4222
 
5.4%
r 3861
 
4.9%
t 3378
 
4.3%
s 3153
 
4.0%
l 2473
 
3.1%
Other values (65) 30213
38.4%
Cyrillic
ValueCountFrequency (%)
о 307
 
8.4%
е 302
 
8.2%
а 288
 
7.8%
и 244
 
6.6%
р 222
 
6.0%
н 212
 
5.8%
с 172
 
4.7%
т 171
 
4.7%
д 140
 
3.8%
я 139
 
3.8%
Other values (47) 1479
40.2%
None
ValueCountFrequency (%)
ü 67
17.3%
ı 54
13.9%
ş 44
11.3%
å 33
 
8.5%
ñ 32
 
8.2%
ö 15
 
3.9%
ø 14
 
3.6%
ä 14
 
3.6%
Ó 12
 
3.1%
â 12
 
3.1%
Other values (22) 91
23.5%
Punctuation
ValueCountFrequency (%)
12
80.0%
3
 
20.0%
Geometric Shapes
ValueCountFrequency (%)
4
100.0%

_embedded_show_id
Real number (ℝ)

High correlation 

Distinct681
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63465.946
Minimum274
Maximum80412
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:46.231163image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum274
5-th percentile11836.8
Q159613
median72501
Q374045
95-th percentile77398.2
Maximum80412
Range80138
Interquartile range (IQR)14432

Descriptive statistics

Standard deviation18711.733
Coefficient of variation (CV)0.29483108
Kurtosis3.2219027
Mean63465.946
Median Absolute Deviation (MAD)3716
Skewness-1.9800069
Sum3.0038432 × 108
Variance3.5012897 × 108
MonotonicityNot monotonic
2024-10-29T14:34:46.366081image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
78854 100
 
2.1%
73952 38
 
0.8%
73773 36
 
0.8%
72654 36
 
0.8%
73703 36
 
0.8%
74045 34
 
0.7%
42056 33
 
0.7%
69806 32
 
0.7%
73931 30
 
0.6%
74100 28
 
0.6%
Other values (671) 4330
91.5%
ValueCountFrequency (%)
274 6
 
0.1%
703 4
 
0.1%
718 17
0.4%
729 4
 
0.1%
793 19
0.4%
802 5
 
0.1%
812 23
0.5%
875 3
 
0.1%
920 8
 
0.2%
938 6
 
0.1%
ValueCountFrequency (%)
80412 1
 
< 0.1%
80352 2
 
< 0.1%
80138 4
 
0.1%
80137 2
 
< 0.1%
79953 2
 
< 0.1%
79903 23
 
0.5%
79454 8
 
0.2%
79449 1
 
< 0.1%
78906 2
 
< 0.1%
78854 100
2.1%
Distinct681
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size504.9 KiB
https://www.tvmaze.com/shows/78854/my-beautiful-dumb-wife
 
100
https://www.tvmaze.com/shows/73952/shanghai-picked-flowers
 
38
https://www.tvmaze.com/shows/73773/my-boss
 
36
https://www.tvmaze.com/shows/72654/our-interpreter
 
36
https://www.tvmaze.com/shows/73703/just-between-us
 
36
Other values (676)
4487 
ValueCountFrequency (%)
https://www.tvmaze.com/shows/78854/my-beautiful-dumb-wife 100
 
2.1%
https://www.tvmaze.com/shows/73952/shanghai-picked-flowers 38
 
0.8%
https://www.tvmaze.com/shows/73773/my-boss 36
 
0.8%
https://www.tvmaze.com/shows/72654/our-interpreter 36
 
0.8%
https://www.tvmaze.com/shows/73703/just-between-us 36
 
0.8%
https://www.tvmaze.com/shows/74045/sword-and-fairy-4 34
 
0.7%
https://www.tvmaze.com/shows/42056/like-a-flowing-river 33
 
0.7%
https://www.tvmaze.com/shows/69806/scout-hero 32
 
0.7%
https://www.tvmaze.com/shows/73931/different-princess 30
 
0.6%
https://www.tvmaze.com/shows/74100/small-town-stories 28
 
0.6%
Other values (671) 4330
91.5%
ValueCountFrequency (%)
https 4733
100.0%
ValueCountFrequency (%)
www.tvmaze.com 4733
100.0%
ValueCountFrequency (%)
/shows/78854/my-beautiful-dumb-wife 100
 
2.1%
/shows/73952/shanghai-picked-flowers 38
 
0.8%
/shows/73773/my-boss 36
 
0.8%
/shows/72654/our-interpreter 36
 
0.8%
/shows/73703/just-between-us 36
 
0.8%
/shows/74045/sword-and-fairy-4 34
 
0.7%
/shows/42056/like-a-flowing-river 33
 
0.7%
/shows/69806/scout-hero 32
 
0.7%
/shows/73931/different-princess 30
 
0.6%
/shows/74100/small-town-stories 28
 
0.6%
Other values (671) 4330
91.5%
ValueCountFrequency (%)
4733
100.0%
ValueCountFrequency (%)
4733
100.0%
Distinct679
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size375.2 KiB
2024-10-29T14:34:46.691833image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length63
Median length41
Mean length17.485527
Min length2

Characters and Unicode

Total characters82759
Distinct characters167
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)1.8%

Sample

1st rowНежность
2nd rowНежность
3rd rowНежность
4th rowНежность
5th rowНежность
ValueCountFrequency (%)
the 777
 
5.2%
of 340
 
2.3%
my 226
 
1.5%
love 179
 
1.2%
news 171
 
1.2%
a 169
 
1.1%
and 160
 
1.1%
with 130
 
0.9%
you 122
 
0.8%
world 108
 
0.7%
Other values (1394) 12453
83.9%
2024-10-29T14:34:47.146796image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10102
 
12.2%
e 7415
 
9.0%
a 5003
 
6.0%
o 4569
 
5.5%
i 4287
 
5.2%
n 4222
 
5.1%
r 3861
 
4.7%
t 3378
 
4.1%
s 3153
 
3.8%
l 2473
 
3.0%
Other values (157) 34296
41.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 57480
69.5%
Uppercase Letter 13889
 
16.8%
Space Separator 10102
 
12.2%
Other Punctuation 808
 
1.0%
Decimal Number 338
 
0.4%
Dash Punctuation 112
 
0.1%
Math Symbol 19
 
< 0.1%
Other Symbol 11
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 7415
12.9%
a 5003
 
8.7%
o 4569
 
7.9%
i 4287
 
7.5%
n 4222
 
7.3%
r 3861
 
6.7%
t 3378
 
5.9%
s 3153
 
5.5%
l 2473
 
4.3%
h 2308
 
4.0%
Other values (72) 16811
29.2%
Uppercase Letter
ValueCountFrequency (%)
S 1227
 
8.8%
T 1170
 
8.4%
M 884
 
6.4%
L 845
 
6.1%
B 781
 
5.6%
A 762
 
5.5%
D 675
 
4.9%
C 673
 
4.8%
W 665
 
4.8%
H 621
 
4.5%
Other values (48) 5586
40.2%
Other Punctuation
ValueCountFrequency (%)
: 296
36.6%
' 274
33.9%
& 58
 
7.2%
! 44
 
5.4%
. 37
 
4.6%
, 30
 
3.7%
/ 23
 
2.8%
@ 22
 
2.7%
? 18
 
2.2%
* 3
 
0.4%
Decimal Number
ValueCountFrequency (%)
4 65
19.2%
1 63
18.6%
3 48
14.2%
2 48
14.2%
0 35
10.4%
7 32
9.5%
9 30
8.9%
8 8
 
2.4%
5 5
 
1.5%
6 4
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 100
89.3%
12
 
10.7%
Other Symbol
ValueCountFrequency (%)
° 7
63.6%
4
36.4%
Space Separator
ValueCountFrequency (%)
10102
100.0%
Math Symbol
ValueCountFrequency (%)
+ 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 67679
81.8%
Common 11390
 
13.8%
Cyrillic 3676
 
4.4%
Greek 14
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 7415
 
11.0%
a 5003
 
7.4%
o 4569
 
6.8%
i 4287
 
6.3%
n 4222
 
6.2%
r 3861
 
5.7%
t 3378
 
5.0%
s 3153
 
4.7%
l 2473
 
3.7%
h 2308
 
3.4%
Other values (66) 27010
39.9%
Cyrillic
ValueCountFrequency (%)
о 307
 
8.4%
е 302
 
8.2%
а 288
 
7.8%
и 244
 
6.6%
р 222
 
6.0%
н 212
 
5.8%
с 172
 
4.7%
т 171
 
4.7%
д 140
 
3.8%
я 139
 
3.8%
Other values (47) 1479
40.2%
Common
ValueCountFrequency (%)
10102
88.7%
: 296
 
2.6%
' 274
 
2.4%
- 100
 
0.9%
4 65
 
0.6%
1 63
 
0.6%
& 58
 
0.5%
3 48
 
0.4%
2 48
 
0.4%
! 44
 
0.4%
Other values (17) 292
 
2.6%
Greek
ValueCountFrequency (%)
ς 2
14.3%
Κ 2
14.3%
έ 2
14.3%
τ 2
14.3%
σ 2
14.3%
ω 2
14.3%
λ 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78676
95.1%
Cyrillic 3676
 
4.4%
None 388
 
0.5%
Punctuation 15
 
< 0.1%
Geometric Shapes 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10102
 
12.8%
e 7415
 
9.4%
a 5003
 
6.4%
o 4569
 
5.8%
i 4287
 
5.4%
n 4222
 
5.4%
r 3861
 
4.9%
t 3378
 
4.3%
s 3153
 
4.0%
l 2473
 
3.1%
Other values (65) 30213
38.4%
Cyrillic
ValueCountFrequency (%)
о 307
 
8.4%
е 302
 
8.2%
а 288
 
7.8%
и 244
 
6.6%
р 222
 
6.0%
н 212
 
5.8%
с 172
 
4.7%
т 171
 
4.7%
д 140
 
3.8%
я 139
 
3.8%
Other values (47) 1479
40.2%
None
ValueCountFrequency (%)
ü 67
17.3%
ı 54
13.9%
ş 44
11.3%
å 33
 
8.5%
ñ 32
 
8.2%
ö 15
 
3.9%
ø 14
 
3.6%
ä 14
 
3.6%
Ó 12
 
3.1%
â 12
 
3.1%
Other values (22) 91
23.5%
Punctuation
ValueCountFrequency (%)
12
80.0%
3
 
20.0%
Geometric Shapes
ValueCountFrequency (%)
4
100.0%

_embedded_show_type
Categorical

High correlation 

Distinct11
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size299.8 KiB
Scripted
2216 
Animation
643 
News
534 
Reality
499 
Documentary
324 
Other values (6)
517 

Length

Max length11
Median length10
Mean length7.8396366
Min length4

Characters and Unicode

Total characters37105
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowScripted
2nd rowScripted
3rd rowScripted
4th rowScripted
5th rowScripted

Common Values

ValueCountFrequency (%)
Scripted 2216
46.8%
Animation 643
 
13.6%
News 534
 
11.3%
Reality 499
 
10.5%
Documentary 324
 
6.8%
Talk Show 279
 
5.9%
Game Show 114
 
2.4%
Variety 56
 
1.2%
Sports 53
 
1.1%
Panel Show 14
 
0.3%

Length

2024-10-29T14:34:47.283226image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
scripted 2216
43.1%
animation 643
 
12.5%
news 534
 
10.4%
reality 499
 
9.7%
show 408
 
7.9%
documentary 324
 
6.3%
talk 279
 
5.4%
game 114
 
2.2%
variety 56
 
1.1%
sports 53
 
1.0%
Other values (2) 15
 
0.3%

Most occurring characters

ValueCountFrequency (%)
i 4057
10.9%
t 3791
 
10.2%
e 3757
 
10.1%
S 2677
 
7.2%
r 2650
 
7.1%
c 2540
 
6.8%
p 2269
 
6.1%
d 2217
 
6.0%
a 1930
 
5.2%
n 1624
 
4.4%
Other values (18) 9593
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 31556
85.0%
Uppercase Letter 5141
 
13.9%
Space Separator 408
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 4057
12.9%
t 3791
12.0%
e 3757
11.9%
r 2650
8.4%
c 2540
8.0%
p 2269
7.2%
d 2217
7.0%
a 1930
 
6.1%
n 1624
 
5.1%
o 1428
 
4.5%
Other values (8) 5293
16.8%
Uppercase Letter
ValueCountFrequency (%)
S 2677
52.1%
A 644
 
12.5%
N 534
 
10.4%
R 499
 
9.7%
D 324
 
6.3%
T 279
 
5.4%
G 114
 
2.2%
V 56
 
1.1%
P 14
 
0.3%
Space Separator
ValueCountFrequency (%)
408
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36697
98.9%
Common 408
 
1.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 4057
11.1%
t 3791
10.3%
e 3757
10.2%
S 2677
 
7.3%
r 2650
 
7.2%
c 2540
 
6.9%
p 2269
 
6.2%
d 2217
 
6.0%
a 1930
 
5.3%
n 1624
 
4.4%
Other values (17) 9185
25.0%
Common
ValueCountFrequency (%)
408
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37105
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 4057
10.9%
t 3791
 
10.2%
e 3757
 
10.1%
S 2677
 
7.2%
r 2650
 
7.1%
c 2540
 
6.8%
p 2269
 
6.1%
d 2217
 
6.0%
a 1930
 
5.2%
n 1624
 
4.4%
Other values (18) 9593
25.9%

_embedded_show_language
Categorical

High correlation  Missing 

Distinct33
Distinct (%)0.7%
Missing310
Missing (%)6.5%
Memory size295.9 KiB
English
1635 
Chinese
1506 
Russian
242 
Norwegian
177 
Korean
 
106
Other values (28)
757 

Length

Max length10
Median length7
Mean length6.9961565
Min length4

Characters and Unicode

Total characters30944
Distinct characters42
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowRussian

Common Values

ValueCountFrequency (%)
English 1635
34.5%
Chinese 1506
31.8%
Russian 242
 
5.1%
Norwegian 177
 
3.7%
Korean 106
 
2.2%
Spanish 86
 
1.8%
Arabic 76
 
1.6%
Swedish 73
 
1.5%
Japanese 69
 
1.5%
Hindi 66
 
1.4%
Other values (23) 387
 
8.2%
(Missing) 310
 
6.5%

Length

2024-10-29T14:34:47.398978image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english 1635
37.0%
chinese 1506
34.0%
russian 242
 
5.5%
norwegian 177
 
4.0%
korean 106
 
2.4%
spanish 86
 
1.9%
arabic 76
 
1.7%
swedish 73
 
1.7%
japanese 69
 
1.6%
hindi 66
 
1.5%
Other values (23) 387
 
8.7%

Most occurring characters

ValueCountFrequency (%)
i 4226
13.7%
n 4164
13.5%
s 4014
13.0%
e 3621
11.7%
h 3522
11.4%
g 1850
6.0%
l 1714
5.5%
E 1635
 
5.3%
C 1516
 
4.9%
a 1153
 
3.7%
Other values (32) 3529
11.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 26521
85.7%
Uppercase Letter 4423
 
14.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 4226
15.9%
n 4164
15.7%
s 4014
15.1%
e 3621
13.7%
h 3522
13.3%
g 1850
7.0%
l 1714
6.5%
a 1153
 
4.3%
r 554
 
2.1%
u 378
 
1.4%
Other values (13) 1325
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
E 1635
37.0%
C 1516
34.3%
R 242
 
5.5%
N 177
 
4.0%
S 160
 
3.6%
K 106
 
2.4%
T 106
 
2.4%
A 93
 
2.1%
H 89
 
2.0%
J 69
 
1.6%
Other values (9) 230
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 30944
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 4226
13.7%
n 4164
13.5%
s 4014
13.0%
e 3621
11.7%
h 3522
11.4%
g 1850
6.0%
l 1714
5.5%
E 1635
 
5.3%
C 1516
 
4.9%
a 1153
 
3.7%
Other values (32) 3529
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30944
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 4226
13.7%
n 4164
13.5%
s 4014
13.0%
e 3621
11.7%
h 3522
11.4%
g 1850
6.0%
l 1714
5.5%
E 1635
 
5.3%
C 1516
 
4.9%
a 1153
 
3.7%
Other values (32) 3529
11.4%

_embedded_show_genres
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size554.8 KiB

_embedded_show_status
Categorical

High correlation 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size298.4 KiB
Running
2386 
Ended
1696 
To Be Determined
651 

Length

Max length16
Median length7
Mean length7.5212339
Min length5

Characters and Unicode

Total characters35598
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEnded
2nd rowEnded
3rd rowEnded
4th rowEnded
5th rowEnded

Common Values

ValueCountFrequency (%)
Running 2386
50.4%
Ended 1696
35.8%
To Be Determined 651
 
13.8%

Length

2024-10-29T14:34:47.509686image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-29T14:34:47.593660image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
running 2386
39.5%
ended 1696
28.1%
to 651
 
10.8%
be 651
 
10.8%
determined 651
 
10.8%

Most occurring characters

ValueCountFrequency (%)
n 9505
26.7%
e 4300
12.1%
d 4043
11.4%
i 3037
 
8.5%
R 2386
 
6.7%
u 2386
 
6.7%
g 2386
 
6.7%
E 1696
 
4.8%
1302
 
3.7%
T 651
 
1.8%
Other values (6) 3906
11.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 28261
79.4%
Uppercase Letter 6035
 
17.0%
Space Separator 1302
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 9505
33.6%
e 4300
15.2%
d 4043
14.3%
i 3037
 
10.7%
u 2386
 
8.4%
g 2386
 
8.4%
o 651
 
2.3%
t 651
 
2.3%
r 651
 
2.3%
m 651
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
R 2386
39.5%
E 1696
28.1%
T 651
 
10.8%
B 651
 
10.8%
D 651
 
10.8%
Space Separator
ValueCountFrequency (%)
1302
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34296
96.3%
Common 1302
 
3.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 9505
27.7%
e 4300
12.5%
d 4043
11.8%
i 3037
 
8.9%
R 2386
 
7.0%
u 2386
 
7.0%
g 2386
 
7.0%
E 1696
 
4.9%
T 651
 
1.9%
o 651
 
1.9%
Other values (5) 3255
 
9.5%
Common
ValueCountFrequency (%)
1302
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35598
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 9505
26.7%
e 4300
12.1%
d 4043
11.4%
i 3037
 
8.5%
R 2386
 
6.7%
u 2386
 
6.7%
g 2386
 
6.7%
E 1696
 
4.8%
1302
 
3.7%
T 651
 
1.8%
Other values (6) 3906
11.0%

_embedded_show_runtime
Real number (ℝ)

High correlation  Missing 

Distinct49
Distinct (%)4.1%
Missing3533
Missing (%)74.6%
Infinite0
Infinite (%)0.0%
Mean60.8525
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:47.696656image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q120
median45
Q360
95-th percentile240
Maximum300
Range299
Interquartile range (IQR)40

Descriptive statistics

Standard deviation61.993333
Coefficient of variation (CV)1.0187475
Kurtosis4.4694286
Mean60.8525
Median Absolute Deviation (MAD)20
Skewness2.1092842
Sum73023
Variance3843.1734
MonotonicityNot monotonic
2024-10-29T14:34:47.818111image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
60 290
 
6.1%
120 106
 
2.2%
30 88
 
1.9%
10 71
 
1.5%
45 71
 
1.5%
12 48
 
1.0%
240 47
 
1.0%
25 40
 
0.8%
20 40
 
0.8%
11 29
 
0.6%
Other values (39) 370
 
7.8%
(Missing) 3533
74.6%
ValueCountFrequency (%)
1 6
 
0.1%
2 12
 
0.3%
3 2
 
< 0.1%
4 2
 
< 0.1%
5 25
 
0.5%
6 2
 
< 0.1%
7 8
 
0.2%
8 20
 
0.4%
10 71
1.5%
11 29
0.6%
ValueCountFrequency (%)
300 23
 
0.5%
240 47
1.0%
210 3
 
0.1%
180 2
 
< 0.1%
159 27
 
0.6%
150 3
 
0.1%
120 106
2.2%
90 12
 
0.3%
75 11
 
0.2%
70 10
 
0.2%

_embedded_show_averageRuntime
Real number (ℝ)

High correlation  Missing 

Distinct101
Distinct (%)2.3%
Missing300
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean44.484548
Minimum1
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:47.944003image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q118
median41
Q352
95-th percentile120
Maximum300
Range299
Interquartile range (IQR)34

Descriptive statistics

Standard deviation42.939376
Coefficient of variation (CV)0.96526497
Kurtosis12.185279
Mean44.484548
Median Absolute Deviation (MAD)17
Skewness3.1011309
Sum197200
Variance1843.79
MonotonicityNot monotonic
2024-10-29T14:34:48.072004image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45 576
 
12.2%
60 334
 
7.1%
15 312
 
6.6%
30 247
 
5.2%
10 220
 
4.6%
43 140
 
3.0%
120 136
 
2.9%
3 119
 
2.5%
25 105
 
2.2%
40 97
 
2.0%
Other values (91) 2147
45.4%
(Missing) 300
 
6.3%
ValueCountFrequency (%)
1 6
 
0.1%
2 42
 
0.9%
3 119
2.5%
4 3
 
0.1%
5 33
 
0.7%
6 9
 
0.2%
7 52
 
1.1%
8 39
 
0.8%
9 19
 
0.4%
10 220
4.6%
ValueCountFrequency (%)
300 23
 
0.5%
242 2
 
< 0.1%
240 69
1.5%
218 1
 
< 0.1%
194 1
 
< 0.1%
184 1
 
< 0.1%
180 30
0.6%
177 4
 
0.1%
164 3
 
0.1%
163 27
 
0.6%
Distinct455
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size37.1 KiB
Minimum1944-01-20 00:00:00
Maximum2024-02-09 00:00:00
2024-10-29T14:34:48.192869image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:48.323538image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

_embedded_show_ended
Date

Missing 

Distinct75
Distinct (%)4.4%
Missing3037
Missing (%)64.2%
Memory size37.1 KiB
Minimum2024-01-01 00:00:00
Maximum2024-11-09 00:00:00
2024-10-29T14:34:48.560697image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:48.690945image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct606
Distinct (%)14.1%
Missing442
Missing (%)9.3%
Memory size473.1 KiB
https://flameserial.ru/season/12949
 
100
https://abcnews.go.com/Live
 
92
https://v.qq.com/x/cover/mzc002005kvupzf.html
 
38
https://w.mgtv.com/h/600824/20020678.html
 
36
https://w.mgtv.com/b/610526/20301892.html?fpa=se&lastp=so_result
 
36
Other values (601)
3989 
(Missing)
442 
ValueCountFrequency (%)
https://flameserial.ru/season/12949 100
 
2.1%
https://abcnews.go.com/Live 92
 
1.9%
https://v.qq.com/x/cover/mzc002005kvupzf.html 38
 
0.8%
https://w.mgtv.com/h/600824/20020678.html 36
 
0.8%
https://w.mgtv.com/b/610526/20301892.html?fpa=se&lastp=so_result 36
 
0.8%
https://v.youku.com/v_nextstage/id_ebdb60223f3e44c7aadf.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle 36
 
0.8%
https://www.iq.com/album/sword-and-fairy-4-2024-13ndvpx4xm1?lang=en_us 34
 
0.7%
https://v.qq.com/x/cover/mzc00200syv5tor.html 33
 
0.7%
https://www.iq.com/album/scout-hero-2023-1oipynj6bzh?lang=en_us 32
 
0.7%
https://v.youku.com/v_show/id_XNjI5ODc3MDM1Mg==.html 30
 
0.6%
Other values (596) 3824
80.8%
(Missing) 442
 
9.3%
ValueCountFrequency (%)
https 4072
86.0%
http 219
 
4.6%
(Missing) 442
 
9.3%
ValueCountFrequency (%)
v.qq.com 617
 
13.0%
www.bbc.co.uk 299
 
6.3%
v.youku.com 247
 
5.2%
www.netflix.com 237
 
5.0%
www.youtube.com 214
 
4.5%
www.iq.com 175
 
3.7%
www.iqiyi.com 125
 
2.6%
w.mgtv.com 108
 
2.3%
flameserial.ru 100
 
2.1%
abcnews.go.com 92
 
1.9%
Other values (192) 2077
43.9%
(Missing) 442
 
9.3%
ValueCountFrequency (%)
/season/12949 100
 
2.1%
/ 99
 
2.1%
/Live 92
 
1.9%
/playlist 59
 
1.2%
/x/cover/mzc002005kvupzf.html 38
 
0.8%
/h/600824/20020678.html 36
 
0.8%
/b/610526/20301892.html 36
 
0.8%
/v_nextstage/id_ebdb60223f3e44c7aadf.html 36
 
0.8%
/album/sword-and-fairy-4-2024-13ndvpx4xm1 34
 
0.7%
/x/cover/mzc00200syv5tor.html 33
 
0.7%
Other values (544) 3728
78.8%
(Missing) 442
 
9.3%
ValueCountFrequency (%)
3713
78.4%
lang=en_us 171
 
3.6%
spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle 144
 
3.0%
fpa=se&lastp=so_result 36
 
0.8%
&s=eacdafb09f604595bcb6 15
 
0.3%
authorId=3xn54kwp9xhww5w&streamSource=profile&area=profilexxnull&currentPcursor=1.707472800354E12 13
 
0.3%
spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=ccad226d231a4184b735 12
 
0.3%
ysclid=lpbaiai0cw654763598 12
 
0.3%
q=无上神帝&stag=&smartbox_ab= 9
 
0.2%
spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=fcae06d654bd4a15b269 9
 
0.2%
Other values (46) 157
 
3.3%
(Missing) 442
 
9.3%
ValueCountFrequency (%)
4286
90.6%
detail 5
 
0.1%
(Missing) 442
 
9.3%

_embedded_show_schedule_time
Categorical

High correlation  Imbalance 

Distinct47
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size273.4 KiB
2714 
12:00
440 
10:00
 
265
18:00
 
237
20:00
 
96
Other values (42)
981 

Length

Max length5
Median length0
Mean length2.1328967
Min length0

Characters and Unicode

Total characters10095
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
2714
57.3%
12:00 440
 
9.3%
10:00 265
 
5.6%
18:00 237
 
5.0%
20:00 96
 
2.0%
21:00 81
 
1.7%
13:00 78
 
1.6%
19:00 76
 
1.6%
06:00 74
 
1.6%
07:00 72
 
1.5%
Other values (37) 600
 
12.7%

Length

2024-10-29T14:34:48.806909image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
12:00 440
21.8%
10:00 265
13.1%
18:00 237
11.7%
20:00 96
 
4.8%
21:00 81
 
4.0%
13:00 78
 
3.9%
19:00 76
 
3.8%
06:00 74
 
3.7%
07:00 72
 
3.6%
09:00 64
 
3.2%
Other values (36) 536
26.5%

Most occurring characters

ValueCountFrequency (%)
0 4413
43.7%
: 2019
20.0%
1 1540
 
15.3%
2 878
 
8.7%
3 330
 
3.3%
8 247
 
2.4%
9 242
 
2.4%
7 157
 
1.6%
6 130
 
1.3%
5 109
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8076
80.0%
Other Punctuation 2019
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4413
54.6%
1 1540
 
19.1%
2 878
 
10.9%
3 330
 
4.1%
8 247
 
3.1%
9 242
 
3.0%
7 157
 
1.9%
6 130
 
1.6%
5 109
 
1.3%
4 30
 
0.4%
Other Punctuation
ValueCountFrequency (%)
: 2019
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10095
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4413
43.7%
: 2019
20.0%
1 1540
 
15.3%
2 878
 
8.7%
3 330
 
3.3%
8 247
 
2.4%
9 242
 
2.4%
7 157
 
1.6%
6 130
 
1.3%
5 109
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10095
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4413
43.7%
: 2019
20.0%
1 1540
 
15.3%
2 878
 
8.7%
3 330
 
3.3%
8 247
 
2.4%
9 242
 
2.4%
7 157
 
1.6%
6 130
 
1.3%
5 109
 
1.1%

_embedded_show_schedule_days
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size554.8 KiB

_embedded_show_rating_average
Real number (ℝ)

High correlation  Missing 

Distinct40
Distinct (%)5.6%
Missing4022
Missing (%)85.0%
Infinite0
Infinite (%)0.0%
Mean6.4229255
Minimum1
Maximum8.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:48.915762image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.3
Q16
median6.8
Q37.3
95-th percentile7.9
Maximum8.2
Range7.2
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation1.3846423
Coefficient of variation (CV)0.21557813
Kurtosis3.7281619
Mean6.4229255
Median Absolute Deviation (MAD)0.6
Skewness-1.7646412
Sum4566.7
Variance1.9172342
MonotonicityNot monotonic
2024-10-29T14:34:49.037033image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
7 45
 
1.0%
7.3 42
 
0.9%
7.8 41
 
0.9%
7.2 40
 
0.8%
7.4 36
 
0.8%
6.8 36
 
0.8%
7.1 35
 
0.7%
6.7 34
 
0.7%
6.3 32
 
0.7%
6.6 29
 
0.6%
Other values (30) 341
 
7.2%
(Missing) 4022
85.0%
ValueCountFrequency (%)
1 7
 
0.1%
1.3 8
 
0.2%
2.1 10
0.2%
2.2 2
 
< 0.1%
4.1 6
 
0.1%
4.3 20
0.4%
4.4 19
0.4%
4.7 1
 
< 0.1%
4.8 24
0.5%
5 7
 
0.1%
ValueCountFrequency (%)
8.2 3
 
0.1%
8.1 4
 
0.1%
8 19
0.4%
7.9 15
 
0.3%
7.8 41
0.9%
7.7 27
0.6%
7.6 6
 
0.1%
7.5 12
 
0.3%
7.4 36
0.8%
7.3 42
0.9%

_embedded_show_weight
Real number (ℝ)

High correlation  Zeros 

Distinct96
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.429749
Minimum0
Maximum100
Zeros135
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:49.161733image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median22
Q351
95-th percentile94
Maximum100
Range100
Interquartile range (IQR)45

Descriptive statistics

Standard deviation30.003705
Coefficient of variation (CV)0.95462757
Kurtosis-0.54813869
Mean31.429749
Median Absolute Deviation (MAD)16
Skewness0.8714533
Sum148757
Variance900.22229
MonotonicityNot monotonic
2024-10-29T14:34:49.285125image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 730
 
15.4%
8 277
 
5.9%
12 170
 
3.6%
3 169
 
3.6%
4 166
 
3.5%
23 151
 
3.2%
0 135
 
2.9%
18 130
 
2.7%
1 103
 
2.2%
9 89
 
1.9%
Other values (86) 2613
55.2%
ValueCountFrequency (%)
0 135
 
2.9%
1 103
 
2.2%
2 55
 
1.2%
3 169
 
3.6%
4 166
 
3.5%
5 53
 
1.1%
6 730
15.4%
7 70
 
1.5%
8 277
 
5.9%
9 89
 
1.9%
ValueCountFrequency (%)
100 3
 
0.1%
99 14
 
0.3%
98 45
1.0%
97 31
 
0.7%
96 41
0.9%
95 49
1.0%
94 84
1.8%
93 31
 
0.7%
92 12
 
0.3%
91 14
 
0.3%

_embedded_show_network
Unsupported

Missing  Rejected  Unsupported 

Missing4733
Missing (%)100.0%
Memory size37.1 KiB

_embedded_show_webChannel_id
Real number (ℝ)

High correlation  Missing 

Distinct143
Distinct (%)3.1%
Missing112
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean196.0435
Minimum1
Maximum643
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:49.404137image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q151
median104
Q3327
95-th percentile616
Maximum643
Range642
Interquartile range (IQR)276

Descriptive statistics

Standard deviation193.55089
Coefficient of variation (CV)0.98728545
Kurtosis-0.22246847
Mean196.0435
Median Absolute Deviation (MAD)83
Skewness1.0264022
Sum905917
Variance37461.948
MonotonicityNot monotonic
2024-10-29T14:34:49.537197image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
104 660
 
13.9%
21 348
 
7.4%
118 304
 
6.4%
26 299
 
6.3%
67 293
 
6.2%
1 247
 
5.2%
619 132
 
2.8%
86 127
 
2.7%
226 108
 
2.3%
3 99
 
2.1%
Other values (133) 2004
42.3%
(Missing) 112
 
2.4%
ValueCountFrequency (%)
1 247
5.2%
2 47
 
1.0%
3 99
 
2.1%
11 26
 
0.5%
12 4
 
0.1%
15 22
 
0.5%
20 12
 
0.3%
21 348
7.4%
26 299
6.3%
30 3
 
0.1%
ValueCountFrequency (%)
643 10
 
0.2%
632 8
 
0.2%
628 4
 
0.1%
623 45
 
1.0%
619 132
2.8%
616 92
1.9%
612 4
 
0.1%
609 6
 
0.1%
607 97
2.0%
600 8
 
0.2%
Distinct142
Distinct (%)3.1%
Missing112
Missing (%)2.4%
Memory size302.6 KiB
2024-10-29T14:34:49.851269image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length8.28219
Min length3

Characters and Unicode

Total characters38272
Distinct characters80
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)0.2%

Sample

1st rowИви
2nd rowИви
3rd rowИви
4th rowИви
5th rowИви
ValueCountFrequency (%)
tencent 660
 
9.4%
qq 660
 
9.4%
youtube 348
 
4.9%
youku 304
 
4.3%
bbc 299
 
4.2%
iplayer 299
 
4.2%
iqiyi 293
 
4.2%
tv 282
 
4.0%
netflix 247
 
3.5%
news 189
 
2.7%
Other values (171) 3472
49.2%
2024-10-29T14:34:50.270580image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3920
 
10.2%
2432
 
6.4%
n 2380
 
6.2%
i 2235
 
5.8%
o 1793
 
4.7%
a 1685
 
4.4%
Q 1613
 
4.2%
t 1608
 
4.2%
T 1583
 
4.1%
u 1565
 
4.1%
Other values (70) 17458
45.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23630
61.7%
Uppercase Letter 11713
30.6%
Space Separator 2432
 
6.4%
Math Symbol 232
 
0.6%
Decimal Number 179
 
0.5%
Other Punctuation 86
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3920
16.6%
n 2380
10.1%
i 2235
9.5%
o 1793
 
7.6%
a 1685
 
7.1%
t 1608
 
6.8%
u 1565
 
6.6%
l 1234
 
5.2%
r 980
 
4.1%
c 954
 
4.0%
Other values (29) 5276
22.3%
Uppercase Letter
ValueCountFrequency (%)
Q 1613
13.8%
T 1583
13.5%
N 992
8.5%
B 972
8.3%
Y 951
8.1%
C 857
7.3%
I 841
7.2%
P 811
 
6.9%
V 682
 
5.8%
W 313
 
2.7%
Other values (22) 2098
17.9%
Other Punctuation
ValueCountFrequency (%)
. 46
53.5%
! 25
29.1%
: 13
 
15.1%
/ 2
 
2.3%
Math Symbol
ValueCountFrequency (%)
+ 228
98.3%
| 4
 
1.7%
Decimal Number
ValueCountFrequency (%)
2 130
72.6%
4 49
 
27.4%
Space Separator
ValueCountFrequency (%)
2432
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34830
91.0%
Common 2929
 
7.7%
Cyrillic 513
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3920
 
11.3%
n 2380
 
6.8%
i 2235
 
6.4%
o 1793
 
5.1%
a 1685
 
4.8%
Q 1613
 
4.6%
t 1608
 
4.6%
T 1583
 
4.5%
u 1565
 
4.5%
l 1234
 
3.5%
Other values (40) 15214
43.7%
Cyrillic
ValueCountFrequency (%)
и 99
19.3%
о 81
15.8%
м 42
8.2%
д 39
 
7.6%
В 36
 
7.0%
е 36
 
7.0%
т 21
 
4.1%
С 21
 
4.1%
р 21
 
4.1%
И 18
 
3.5%
Other values (11) 99
19.3%
Common
ValueCountFrequency (%)
2432
83.0%
+ 228
 
7.8%
2 130
 
4.4%
4 49
 
1.7%
. 46
 
1.6%
! 25
 
0.9%
: 13
 
0.4%
| 4
 
0.1%
/ 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37759
98.7%
Cyrillic 513
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 3920
 
10.4%
2432
 
6.4%
n 2380
 
6.3%
i 2235
 
5.9%
o 1793
 
4.7%
a 1685
 
4.5%
Q 1613
 
4.3%
t 1608
 
4.3%
T 1583
 
4.2%
u 1565
 
4.1%
Other values (49) 16945
44.9%
Cyrillic
ValueCountFrequency (%)
и 99
19.3%
о 81
15.8%
м 42
8.2%
д 39
 
7.6%
В 36
 
7.0%
е 36
 
7.0%
т 21
 
4.1%
С 21
 
4.1%
р 21
 
4.1%
И 18
 
3.5%
Other values (11) 99
19.3%

_embedded_show_webChannel_country_name
Categorical

High correlation  Missing 

Distinct32
Distinct (%)1.0%
Missing1595
Missing (%)33.7%
Memory size302.4 KiB
China
1264 
United States
641 
United Kingdom
368 
Russian Federation
210 
Norway
140 
Other values (27)
515 

Length

Max length25
Median length18
Mean length9.0984704
Min length5

Characters and Unicode

Total characters28551
Distinct characters44
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowRussian Federation
4th rowRussian Federation
5th rowRussian Federation

Common Values

ValueCountFrequency (%)
China 1264
26.7%
United States 641
13.5%
United Kingdom 368
 
7.8%
Russian Federation 210
 
4.4%
Norway 140
 
3.0%
India 72
 
1.5%
Canada 71
 
1.5%
Sweden 65
 
1.4%
Korea, Republic of 56
 
1.2%
Turkey 27
 
0.6%
Other values (22) 224
 
4.7%
(Missing) 1595
33.7%

Length

2024-10-29T14:34:50.404631image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
china 1273
28.3%
united 1009
22.4%
states 641
14.2%
kingdom 368
 
8.2%
russian 210
 
4.7%
federation 210
 
4.7%
norway 140
 
3.1%
india 72
 
1.6%
canada 71
 
1.6%
sweden 65
 
1.4%
Other values (28) 441
 
9.8%

Most occurring characters

ValueCountFrequency (%)
n 3424
12.0%
i 3352
11.7%
a 3032
10.6%
t 2587
 
9.1%
e 2440
 
8.5%
d 1830
 
6.4%
1362
 
4.8%
C 1344
 
4.7%
h 1302
 
4.6%
s 1107
 
3.9%
Other values (34) 6771
23.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22689
79.5%
Uppercase Letter 4435
 
15.5%
Space Separator 1362
 
4.8%
Other Punctuation 65
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 3424
15.1%
i 3352
14.8%
a 3032
13.4%
t 2587
11.4%
e 2440
10.8%
d 1830
8.1%
h 1302
 
5.7%
s 1107
 
4.9%
o 870
 
3.8%
r 533
 
2.3%
Other values (14) 2212
9.7%
Uppercase Letter
ValueCountFrequency (%)
C 1344
30.3%
U 1012
22.8%
S 724
16.3%
K 424
 
9.6%
R 266
 
6.0%
F 225
 
5.1%
N 144
 
3.2%
I 86
 
1.9%
T 42
 
0.9%
P 32
 
0.7%
Other values (8) 136
 
3.1%
Space Separator
ValueCountFrequency (%)
1362
100.0%
Other Punctuation
ValueCountFrequency (%)
, 65
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 27124
95.0%
Common 1427
 
5.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 3424
12.6%
i 3352
12.4%
a 3032
11.2%
t 2587
9.5%
e 2440
9.0%
d 1830
 
6.7%
C 1344
 
5.0%
h 1302
 
4.8%
s 1107
 
4.1%
U 1012
 
3.7%
Other values (32) 5694
21.0%
Common
ValueCountFrequency (%)
1362
95.4%
, 65
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 3424
12.0%
i 3352
11.7%
a 3032
10.6%
t 2587
 
9.1%
e 2440
 
8.5%
d 1830
 
6.4%
1362
 
4.8%
C 1344
 
4.7%
h 1302
 
4.6%
s 1107
 
3.9%
Other values (34) 6771
23.7%

_embedded_show_webChannel_country_code
Categorical

High correlation  Missing 

Distinct32
Distinct (%)1.0%
Missing1595
Missing (%)33.7%
Memory size280.6 KiB
CN
1264 
US
641 
GB
368 
RU
210 
NO
140 
Other values (27)
515 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters6276
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowRU
2nd rowRU
3rd rowRU
4th rowRU
5th rowRU

Common Values

ValueCountFrequency (%)
CN 1264
26.7%
US 641
13.5%
GB 368
 
7.8%
RU 210
 
4.4%
NO 140
 
3.0%
IN 72
 
1.5%
CA 71
 
1.5%
SE 65
 
1.4%
KR 56
 
1.2%
TR 27
 
0.6%
Other values (22) 224
 
4.7%
(Missing) 1595
33.7%

Length

2024-10-29T14:34:50.520853image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cn 1264
40.3%
us 641
20.4%
gb 368
 
11.7%
ru 210
 
6.7%
no 140
 
4.5%
in 72
 
2.3%
ca 71
 
2.3%
se 65
 
2.1%
kr 56
 
1.8%
tr 27
 
0.9%
Other values (22) 224
 
7.1%

Most occurring characters

ValueCountFrequency (%)
N 1480
23.6%
C 1343
21.4%
U 892
14.2%
S 712
11.3%
G 395
 
6.3%
B 382
 
6.1%
R 297
 
4.7%
O 140
 
2.2%
E 135
 
2.2%
A 105
 
1.7%
Other values (13) 395
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 6276
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1480
23.6%
C 1343
21.4%
U 892
14.2%
S 712
11.3%
G 395
 
6.3%
B 382
 
6.1%
R 297
 
4.7%
O 140
 
2.2%
E 135
 
2.2%
A 105
 
1.7%
Other values (13) 395
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 6276
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1480
23.6%
C 1343
21.4%
U 892
14.2%
S 712
11.3%
G 395
 
6.3%
B 382
 
6.1%
R 297
 
4.7%
O 140
 
2.2%
E 135
 
2.2%
A 105
 
1.7%
Other values (13) 395
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6276
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 1480
23.6%
C 1343
21.4%
U 892
14.2%
S 712
11.3%
G 395
 
6.3%
B 382
 
6.1%
R 297
 
4.7%
O 140
 
2.2%
E 135
 
2.2%
A 105
 
1.7%
Other values (13) 395
 
6.3%

_embedded_show_webChannel_country_timezone
Categorical

High correlation  Missing 

Distinct32
Distinct (%)1.0%
Missing1595
Missing (%)33.7%
Memory size316.4 KiB
Asia/Shanghai
1264 
America/New_York
641 
Europe/London
368 
Asia/Kamchatka
210 
Europe/Oslo
140 
Other values (27)
515 

Length

Max length19
Median length13
Mean length13.677183
Min length10

Characters and Unicode

Total characters42919
Distinct characters44
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Kamchatka
5th rowAsia/Kamchatka

Common Values

ValueCountFrequency (%)
Asia/Shanghai 1264
26.7%
America/New_York 641
13.5%
Europe/London 368
 
7.8%
Asia/Kamchatka 210
 
4.4%
Europe/Oslo 140
 
3.0%
Asia/Kolkata 72
 
1.5%
America/Halifax 71
 
1.5%
Europe/Stockholm 65
 
1.4%
Asia/Seoul 56
 
1.2%
Europe/Istanbul 27
 
0.6%
Other values (22) 224
 
4.7%
(Missing) 1595
33.7%

Length

2024-10-29T14:34:50.624687image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asia/shanghai 1264
40.3%
america/new_york 641
20.4%
europe/london 368
 
11.7%
asia/kamchatka 210
 
6.7%
europe/oslo 140
 
4.5%
asia/kolkata 72
 
2.3%
america/halifax 71
 
2.3%
europe/stockholm 65
 
2.1%
asia/seoul 56
 
1.8%
europe/istanbul 27
 
0.9%
Other values (22) 224
 
7.1%

Most occurring characters

ValueCountFrequency (%)
a 6031
14.1%
i 3894
 
9.1%
/ 3138
 
7.3%
h 2818
 
6.6%
o 2584
 
6.0%
A 2433
 
5.7%
e 2275
 
5.3%
r 2217
 
5.2%
n 2164
 
5.0%
s 1954
 
4.6%
Other values (34) 13411
31.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32223
75.1%
Uppercase Letter 6917
 
16.1%
Other Punctuation 3138
 
7.3%
Connector Punctuation 641
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 6031
18.7%
i 3894
12.1%
h 2818
8.7%
o 2584
8.0%
e 2275
 
7.1%
r 2217
 
6.9%
n 2164
 
6.7%
s 1954
 
6.1%
g 1300
 
4.0%
c 1034
 
3.2%
Other values (13) 5952
18.5%
Uppercase Letter
ValueCountFrequency (%)
A 2433
35.2%
S 1412
20.4%
E 711
 
10.3%
N 641
 
9.3%
Y 641
 
9.3%
L 372
 
5.4%
K 285
 
4.1%
O 140
 
2.0%
H 84
 
1.2%
B 56
 
0.8%
Other values (9) 142
 
2.1%
Other Punctuation
ValueCountFrequency (%)
/ 3138
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 641
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 39140
91.2%
Common 3779
 
8.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 6031
15.4%
i 3894
 
9.9%
h 2818
 
7.2%
o 2584
 
6.6%
A 2433
 
6.2%
e 2275
 
5.8%
r 2217
 
5.7%
n 2164
 
5.5%
s 1954
 
5.0%
S 1412
 
3.6%
Other values (32) 11358
29.0%
Common
ValueCountFrequency (%)
/ 3138
83.0%
_ 641
 
17.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42919
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 6031
14.1%
i 3894
 
9.1%
/ 3138
 
7.3%
h 2818
 
6.6%
o 2584
 
6.0%
A 2433
 
5.7%
e 2275
 
5.3%
r 2217
 
5.2%
n 2164
 
5.0%
s 1954
 
4.6%
Other values (34) 13411
31.2%
Distinct84
Distinct (%)2.5%
Missing1376
Missing (%)29.1%
Memory size309.0 KiB
https://v.qq.com/
660 
https://www.youtube.com
348 
https://www.bbc.co.uk/iplayer
299 
https://www.iq.com/
293 
https://www.netflix.com/
247 
Other values (79)
1510 
(Missing)
1376 
ValueCountFrequency (%)
https://v.qq.com/ 660
13.9%
https://www.youtube.com 348
 
7.4%
https://www.bbc.co.uk/iplayer 299
 
6.3%
https://www.iq.com/ 293
 
6.2%
https://www.netflix.com/ 247
 
5.2%
https://edition.cnn.com/?hpt=header_edition-picker 132
 
2.8%
https://w.mgtv.com/ 108
 
2.3%
https://www.primevideo.com 99
 
2.1%
https://www.peacocktv.com/ 98
 
2.1%
https://abcnews.go.com/Live 92
 
1.9%
Other values (74) 981
20.7%
(Missing) 1376
29.1%
ValueCountFrequency (%)
https 3343
70.6%
http 14
 
0.3%
(Missing) 1376
29.1%
ValueCountFrequency (%)
v.qq.com 660
13.9%
www.youtube.com 348
 
7.4%
www.bbc.co.uk 299
 
6.3%
www.iq.com 293
 
6.2%
www.netflix.com 247
 
5.2%
edition.cnn.com 132
 
2.8%
w.mgtv.com 108
 
2.3%
www.primevideo.com 99
 
2.1%
www.peacocktv.com 98
 
2.1%
abcnews.go.com 92
 
1.9%
Other values (73) 981
20.7%
(Missing) 1376
29.1%
ValueCountFrequency (%)
/ 2210
46.7%
511
 
10.8%
/iplayer 299
 
6.3%
/Live 92
 
1.9%
/adlp/freevee-about 47
 
1.0%
/n2 45
 
1.0%
/video/@vkvideo 20
 
0.4%
/video 16
 
0.3%
/en 16
 
0.3%
/minitv 15
 
0.3%
Other values (13) 86
 
1.8%
(Missing) 1376
29.1%
ValueCountFrequency (%)
3217
68.0%
hpt=header_edition-picker 132
 
2.8%
utm_source=google&utm_campaign=gads_search_brand&utm_medium=cpc&utm_term=pure%20flix&hsa_ver=3&hsa_grp=68693273966&hsa_acc=9355037628&hsa_ad=676826129706&hsa_src=g&hsa_tgt=kwd-325450860434&hsa_kw=pure%20f 4
 
0.1%
ref=d6k_applink_bb_dls&dplnkId=cf2c8abd-2308-47e3-947b-b9f7e981c117 4
 
0.1%
(Missing) 1376
29.1%
ValueCountFrequency (%)
3357
70.9%
(Missing) 1376
29.1%

_embedded_show_dvdCountry
Unsupported

Missing  Rejected  Unsupported 

Missing4733
Missing (%)100.0%
Memory size37.1 KiB

_embedded_show_externals_tvrage
Real number (ℝ)

High correlation  Missing 

Distinct24
Distinct (%)13.5%
Missing4555
Missing (%)96.2%
Infinite0
Infinite (%)0.0%
Mean16543.444
Minimum712
Maximum47170
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:50.721563image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum712
5-th percentile1888
Q13256
median8531
Q332413
95-th percentile35853
Maximum47170
Range46458
Interquartile range (IQR)29157

Descriptive statistics

Standard deviation14527.157
Coefficient of variation (CV)0.87812173
Kurtosis-1.5450299
Mean16543.444
Median Absolute Deviation (MAD)6643
Skewness0.38256155
Sum2944733
Variance2.110383 × 108
MonotonicityNot monotonic
2024-10-29T14:34:50.819564image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3256 23
 
0.5%
1888 20
 
0.4%
3418 19
 
0.4%
35853 17
 
0.4%
28327 11
 
0.2%
34149 10
 
0.2%
33858 10
 
0.2%
8531 8
 
0.2%
32413 6
 
0.1%
5199 6
 
0.1%
Other values (14) 48
 
1.0%
(Missing) 4555
96.2%
ValueCountFrequency (%)
712 2
 
< 0.1%
1888 20
0.4%
3005 4
 
0.1%
3256 23
0.5%
3418 19
0.4%
4920 4
 
0.1%
5152 4
 
0.1%
5199 6
 
0.1%
6659 5
 
0.1%
8531 8
 
0.2%
ValueCountFrequency (%)
47170 4
 
0.1%
35853 17
0.4%
34149 10
0.2%
33858 10
0.2%
32413 6
 
0.1%
31493 1
 
< 0.1%
30951 5
 
0.1%
28327 11
0.2%
27551 1
 
< 0.1%
26056 6
 
0.1%

_embedded_show_externals_thetvdb
Real number (ℝ)

High correlation  Missing 

Distinct488
Distinct (%)15.0%
Missing1487
Missing (%)31.4%
Infinite0
Infinite (%)0.0%
Mean395286.32
Minimum70366
Maximum449126
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:50.928824image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum70366
5-th percentile182111
Q1391665.5
median431096
Q3443249
95-th percentile444879
Maximum449126
Range378760
Interquartile range (IQR)51583.5

Descriptive statistics

Standard deviation85412.177
Coefficient of variation (CV)0.21607673
Kurtosis6.1972225
Mean395286.32
Median Absolute Deviation (MAD)13187
Skewness-2.5564835
Sum1.2830994 × 109
Variance7.2952399 × 109
MonotonicityNot monotonic
2024-10-29T14:34:51.059357image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
442007 36
 
0.8%
437967 36
 
0.8%
442306 34
 
0.7%
356549 33
 
0.7%
444283 30
 
0.6%
438826 28
 
0.6%
444879 28
 
0.6%
444128 26
 
0.5%
433681 26
 
0.5%
443573 24
 
0.5%
Other values (478) 2945
62.2%
(Missing) 1487
31.4%
ValueCountFrequency (%)
70366 23
0.5%
71178 2
 
< 0.1%
71753 19
0.4%
71756 4
 
0.1%
72716 4
 
0.1%
76355 6
 
0.1%
76719 19
0.4%
76779 5
 
0.1%
78006 20
0.4%
78419 4
 
0.1%
ValueCountFrequency (%)
449126 6
0.1%
448382 10
0.2%
447745 8
0.2%
447710 3
 
0.1%
447439 3
 
0.1%
447332 2
 
< 0.1%
447062 1
 
< 0.1%
446981 13
0.3%
446122 4
 
0.1%
446119 2
 
< 0.1%
Distinct345
Distinct (%)16.2%
Missing2599
Missing (%)54.9%
Memory size220.5 KiB
2024-10-29T14:34:51.315619image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.7614808
Min length9

Characters and Unicode

Total characters20831
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)1.6%

Sample

1st rowtt20603062
2nd rowtt15816496
3rd rowtt19756810
4th rowtt27432264
5th rowtt27801903
ValueCountFrequency (%)
tt29367046 36
 
1.7%
tt9437032 33
 
1.5%
tt24060116 27
 
1.3%
tt15268270 23
 
1.1%
tt19382854 23
 
1.1%
tt27654411 23
 
1.1%
tt21450424 23
 
1.1%
tt0058796 23
 
1.1%
tt29894652 23
 
1.1%
tt30836097 22
 
1.0%
Other values (335) 1878
88.0%
2024-10-29T14:34:51.670114image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 4268
20.5%
2 2284
11.0%
0 2055
9.9%
1 1856
8.9%
4 1810
8.7%
6 1632
 
7.8%
8 1595
 
7.7%
3 1579
 
7.6%
5 1300
 
6.2%
9 1272
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16563
79.5%
Lowercase Letter 4268
 
20.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2284
13.8%
0 2055
12.4%
1 1856
11.2%
4 1810
10.9%
6 1632
9.9%
8 1595
9.6%
3 1579
9.5%
5 1300
7.8%
9 1272
7.7%
7 1180
7.1%
Lowercase Letter
ValueCountFrequency (%)
t 4268
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16563
79.5%
Latin 4268
 
20.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2284
13.8%
0 2055
12.4%
1 1856
11.2%
4 1810
10.9%
6 1632
9.9%
8 1595
9.6%
3 1579
9.5%
5 1300
7.8%
9 1272
7.7%
7 1180
7.1%
Latin
ValueCountFrequency (%)
t 4268
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20831
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 4268
20.5%
2 2284
11.0%
0 2055
9.9%
1 1856
8.9%
4 1810
8.7%
6 1632
 
7.8%
8 1595
 
7.7%
3 1579
 
7.6%
5 1300
 
6.2%
9 1272
 
6.1%
Distinct649
Distinct (%)14.5%
Missing249
Missing (%)5.3%
Memory size572.1 KiB
https://static.tvmaze.com/uploads/images/medium_portrait/530/1326663.jpg
 
100
https://static.tvmaze.com/uploads/images/medium_portrait/499/1249196.jpg
 
38
https://static.tvmaze.com/uploads/images/medium_portrait/497/1243716.jpg
 
36
https://static.tvmaze.com/uploads/images/medium_portrait/498/1246093.jpg
 
36
https://static.tvmaze.com/uploads/images/medium_portrait/486/1216268.jpg
 
36
Other values (644)
4238 
(Missing)
 
249
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/530/1326663.jpg 100
 
2.1%
https://static.tvmaze.com/uploads/images/medium_portrait/499/1249196.jpg 38
 
0.8%
https://static.tvmaze.com/uploads/images/medium_portrait/497/1243716.jpg 36
 
0.8%
https://static.tvmaze.com/uploads/images/medium_portrait/498/1246093.jpg 36
 
0.8%
https://static.tvmaze.com/uploads/images/medium_portrait/486/1216268.jpg 36
 
0.8%
https://static.tvmaze.com/uploads/images/medium_portrait/500/1250432.jpg 34
 
0.7%
https://static.tvmaze.com/uploads/images/medium_portrait/498/1247447.jpg 33
 
0.7%
https://static.tvmaze.com/uploads/images/medium_portrait/468/1170172.jpg 32
 
0.7%
https://static.tvmaze.com/uploads/images/medium_portrait/499/1248923.jpg 30
 
0.6%
https://static.tvmaze.com/uploads/images/medium_portrait/498/1247452.jpg 28
 
0.6%
Other values (639) 4081
86.2%
(Missing) 249
 
5.3%
ValueCountFrequency (%)
https 4484
94.7%
(Missing) 249
 
5.3%
ValueCountFrequency (%)
static.tvmaze.com 4484
94.7%
(Missing) 249
 
5.3%
ValueCountFrequency (%)
/uploads/images/medium_portrait/530/1326663.jpg 100
 
2.1%
/uploads/images/medium_portrait/499/1249196.jpg 38
 
0.8%
/uploads/images/medium_portrait/486/1216268.jpg 36
 
0.8%
/uploads/images/medium_portrait/497/1243716.jpg 36
 
0.8%
/uploads/images/medium_portrait/498/1246093.jpg 36
 
0.8%
/uploads/images/medium_portrait/500/1250432.jpg 34
 
0.7%
/uploads/images/medium_portrait/498/1247447.jpg 33
 
0.7%
/uploads/images/medium_portrait/468/1170172.jpg 32
 
0.7%
/uploads/images/medium_portrait/499/1248923.jpg 30
 
0.6%
/uploads/images/medium_portrait/498/1247452.jpg 28
 
0.6%
Other values (639) 4081
86.2%
(Missing) 249
 
5.3%
ValueCountFrequency (%)
4484
94.7%
(Missing) 249
 
5.3%
ValueCountFrequency (%)
4484
94.7%
(Missing) 249
 
5.3%
Distinct649
Distinct (%)14.5%
Missing249
Missing (%)5.3%
Memory size585.2 KiB
https://static.tvmaze.com/uploads/images/original_untouched/530/1326663.jpg
 
100
https://static.tvmaze.com/uploads/images/original_untouched/499/1249196.jpg
 
38
https://static.tvmaze.com/uploads/images/original_untouched/497/1243716.jpg
 
36
https://static.tvmaze.com/uploads/images/original_untouched/498/1246093.jpg
 
36
https://static.tvmaze.com/uploads/images/original_untouched/486/1216268.jpg
 
36
Other values (644)
4238 
(Missing)
 
249
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/530/1326663.jpg 100
 
2.1%
https://static.tvmaze.com/uploads/images/original_untouched/499/1249196.jpg 38
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/497/1243716.jpg 36
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/498/1246093.jpg 36
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/486/1216268.jpg 36
 
0.8%
https://static.tvmaze.com/uploads/images/original_untouched/500/1250432.jpg 34
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/498/1247447.jpg 33
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/468/1170172.jpg 32
 
0.7%
https://static.tvmaze.com/uploads/images/original_untouched/499/1248923.jpg 30
 
0.6%
https://static.tvmaze.com/uploads/images/original_untouched/498/1247452.jpg 28
 
0.6%
Other values (639) 4081
86.2%
(Missing) 249
 
5.3%
ValueCountFrequency (%)
https 4484
94.7%
(Missing) 249
 
5.3%
ValueCountFrequency (%)
static.tvmaze.com 4484
94.7%
(Missing) 249
 
5.3%
ValueCountFrequency (%)
/uploads/images/original_untouched/530/1326663.jpg 100
 
2.1%
/uploads/images/original_untouched/499/1249196.jpg 38
 
0.8%
/uploads/images/original_untouched/486/1216268.jpg 36
 
0.8%
/uploads/images/original_untouched/497/1243716.jpg 36
 
0.8%
/uploads/images/original_untouched/498/1246093.jpg 36
 
0.8%
/uploads/images/original_untouched/500/1250432.jpg 34
 
0.7%
/uploads/images/original_untouched/498/1247447.jpg 33
 
0.7%
/uploads/images/original_untouched/468/1170172.jpg 32
 
0.7%
/uploads/images/original_untouched/499/1248923.jpg 30
 
0.6%
/uploads/images/original_untouched/498/1247452.jpg 28
 
0.6%
Other values (639) 4081
86.2%
(Missing) 249
 
5.3%
ValueCountFrequency (%)
4484
94.7%
(Missing) 249
 
5.3%
ValueCountFrequency (%)
4484
94.7%
(Missing) 249
 
5.3%
Distinct590
Distinct (%)14.9%
Missing772
Missing (%)16.3%
Memory size2.2 MiB
2024-10-29T14:34:51.958724image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length1931
Median length631
Mean length382.3951
Min length50

Characters and Unicode

Total characters1514667
Distinct characters333
Distinct categories15 ?
Distinct scripts6 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)1.8%

Sample

1st row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
2nd row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
3rd row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
4th row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
5th row<p>30-year-old Sasha is a serial loser trying with all his might to become a successful business coach. Fate leads him to billionaire Oleg Kalugin, who decides to hire the resilient dreamer as a coach. However, Kalugin does not need advice on business, which the guy knows nothing about, but the secret of his ability to sincerely enjoy life despite poverty and other problems. From this moment, drastic changes begin in Sasha's life, which show the real price of success. Step by step, he moves further and further away from happiness, plunging into the world of deception, betrayal, hatred and really big, but dirty money.</p>
ValueCountFrequency (%)
the 15033
 
6.0%
and 9008
 
3.6%
to 7098
 
2.8%
of 7042
 
2.8%
a 6966
 
2.8%
in 4508
 
1.8%
is 2720
 
1.1%
with 2624
 
1.1%
her 2565
 
1.0%
his 2301
 
0.9%
Other values (8249) 189874
76.0%
2024-10-29T14:34:52.399078image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
245423
16.2%
e 144614
 
9.5%
a 95402
 
6.3%
t 95360
 
6.3%
n 88713
 
5.9%
i 87721
 
5.8%
o 83896
 
5.5%
s 76248
 
5.0%
r 71737
 
4.7%
h 64168
 
4.2%
Other values (323) 461385
30.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1155291
76.3%
Space Separator 245816
 
16.2%
Uppercase Letter 42784
 
2.8%
Other Punctuation 39794
 
2.6%
Math Symbol 21571
 
1.4%
Decimal Number 3248
 
0.2%
Dash Punctuation 3039
 
0.2%
Other Letter 2223
 
0.1%
Open Punctuation 408
 
< 0.1%
Close Punctuation 408
 
< 0.1%
Other values (5) 85
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
112
 
5.0%
70
 
3.1%
63
 
2.8%
56
 
2.5%
56
 
2.5%
49
 
2.2%
42
 
1.9%
42
 
1.9%
35
 
1.6%
35
 
1.6%
Other values (165) 1663
74.8%
Lowercase Letter
ValueCountFrequency (%)
e 144614
12.5%
a 95402
 
8.3%
t 95360
 
8.3%
n 88713
 
7.7%
i 87721
 
7.6%
o 83896
 
7.3%
s 76248
 
6.6%
r 71737
 
6.2%
h 64168
 
5.6%
l 46711
 
4.0%
Other values (67) 300721
26.0%
Uppercase Letter
ValueCountFrequency (%)
T 3992
 
9.3%
S 3810
 
8.9%
A 3046
 
7.1%
C 2496
 
5.8%
H 2476
 
5.8%
L 2269
 
5.3%
Y 2204
 
5.2%
M 2113
 
4.9%
B 1778
 
4.2%
J 1671
 
3.9%
Other values (25) 16929
39.6%
Other Punctuation
ValueCountFrequency (%)
, 15657
39.3%
. 11719
29.4%
/ 5537
 
13.9%
' 2924
 
7.3%
" 2125
 
5.3%
! 485
 
1.2%
? 465
 
1.2%
: 300
 
0.8%
; 267
 
0.7%
140
 
0.4%
Other values (6) 175
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 878
27.0%
1 700
21.6%
2 522
16.1%
9 403
12.4%
3 203
 
6.2%
5 129
 
4.0%
4 128
 
3.9%
8 123
 
3.8%
7 92
 
2.8%
6 70
 
2.2%
Math Symbol
ValueCountFrequency (%)
> 10785
50.0%
< 10785
50.0%
+ 1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 2763
90.9%
150
 
4.9%
126
 
4.1%
Currency Symbol
ValueCountFrequency (%)
$ 22
55.0%
£ 12
30.0%
6
 
15.0%
Space Separator
ValueCountFrequency (%)
245423
99.8%
  393
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 390
95.6%
[ 18
 
4.4%
Close Punctuation
ValueCountFrequency (%)
) 390
95.6%
] 18
 
4.4%
Initial Punctuation
ValueCountFrequency (%)
19
90.5%
« 2
 
9.5%
Other Symbol
ValueCountFrequency (%)
11
100.0%
Modifier Letter
ValueCountFrequency (%)
11
100.0%
Final Punctuation
ValueCountFrequency (%)
» 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1197271
79.0%
Common 314369
 
20.8%
Han 2179
 
0.1%
Cyrillic 790
 
0.1%
Katakana 44
 
< 0.1%
Greek 14
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
112
 
5.1%
70
 
3.2%
63
 
2.9%
56
 
2.6%
56
 
2.6%
49
 
2.2%
42
 
1.9%
42
 
1.9%
35
 
1.6%
35
 
1.6%
Other values (161) 1619
74.3%
Latin
ValueCountFrequency (%)
e 144614
12.1%
a 95402
 
8.0%
t 95360
 
8.0%
n 88713
 
7.4%
i 87721
 
7.3%
o 83896
 
7.0%
s 76248
 
6.4%
r 71737
 
6.0%
h 64168
 
5.4%
l 46711
 
3.9%
Other values (57) 342701
28.6%
Common
ValueCountFrequency (%)
245423
78.1%
, 15657
 
5.0%
. 11719
 
3.7%
> 10785
 
3.4%
< 10785
 
3.4%
/ 5537
 
1.8%
' 2924
 
0.9%
- 2763
 
0.9%
" 2125
 
0.7%
0 878
 
0.3%
Other values (36) 5773
 
1.8%
Cyrillic
ValueCountFrequency (%)
о 75
 
9.5%
а 74
 
9.4%
н 67
 
8.5%
е 58
 
7.3%
и 54
 
6.8%
т 49
 
6.2%
р 44
 
5.6%
в 40
 
5.1%
с 40
 
5.1%
м 30
 
3.8%
Other values (28) 259
32.8%
Greek
ValueCountFrequency (%)
ς 2
14.3%
έ 2
14.3%
τ 2
14.3%
σ 2
14.3%
ω 2
14.3%
λ 2
14.3%
Κ 2
14.3%
Katakana
ValueCountFrequency (%)
11
25.0%
11
25.0%
11
25.0%
11
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1510440
99.7%
CJK 2179
 
0.1%
None 820
 
0.1%
Cyrillic 790
 
0.1%
Punctuation 366
 
< 0.1%
Katakana 55
 
< 0.1%
Dingbats 11
 
< 0.1%
Currency Symbols 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
245423
16.2%
e 144614
 
9.6%
a 95402
 
6.3%
t 95360
 
6.3%
n 88713
 
5.9%
i 87721
 
5.8%
o 83896
 
5.6%
s 76248
 
5.0%
r 71737
 
4.7%
h 64168
 
4.2%
Other values (75) 457158
30.3%
None
ValueCountFrequency (%)
  393
47.9%
140
 
17.1%
ä 53
 
6.5%
å 44
 
5.4%
ö 34
 
4.1%
ó 24
 
2.9%
é 23
 
2.8%
á 21
 
2.6%
14
 
1.7%
£ 12
 
1.5%
Other values (18) 62
 
7.6%
Punctuation
ValueCountFrequency (%)
150
41.0%
126
34.4%
71
19.4%
19
 
5.2%
CJK
ValueCountFrequency (%)
112
 
5.1%
70
 
3.2%
63
 
2.9%
56
 
2.6%
56
 
2.6%
49
 
2.2%
42
 
1.9%
42
 
1.9%
35
 
1.6%
35
 
1.6%
Other values (161) 1619
74.3%
Cyrillic
ValueCountFrequency (%)
о 75
 
9.5%
а 74
 
9.4%
н 67
 
8.5%
е 58
 
7.3%
и 54
 
6.8%
т 49
 
6.2%
р 44
 
5.6%
в 40
 
5.1%
с 40
 
5.1%
м 30
 
3.8%
Other values (28) 259
32.8%
Katakana
ValueCountFrequency (%)
11
20.0%
11
20.0%
11
20.0%
11
20.0%
11
20.0%
Dingbats
ValueCountFrequency (%)
11
100.0%
Currency Symbols
ValueCountFrequency (%)
6
100.0%

_embedded_show_updated
Real number (ℝ)

High correlation 

Distinct681
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7156722 × 109
Minimum1.6983432 × 109
Maximum1.730223 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:52.521372image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.6983432 × 109
5-th percentile1.7048164 × 109
Q11.7066956 × 109
median1.7138339 × 109
Q31.7252259 × 109
95-th percentile1.73007 × 109
Maximum1.730223 × 109
Range31879874
Interquartile range (IQR)18530249

Descriptive statistics

Standard deviation9238397.7
Coefficient of variation (CV)0.0053847102
Kurtosis-1.4287318
Mean1.7156722 × 109
Median Absolute Deviation (MAD)7747315
Skewness0.30775926
Sum8.1202766 × 1012
Variance8.5347992 × 1013
MonotonicityNot monotonic
2024-10-29T14:34:52.648512image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1723133542 100
 
2.1%
1707133992 38
 
0.8%
1706282249 36
 
0.8%
1706192291 36
 
0.8%
1705897985 36
 
0.8%
1706797142 34
 
0.7%
1711774278 33
 
0.7%
1706339205 32
 
0.7%
1706957455 30
 
0.6%
1706797129 28
 
0.6%
Other values (671) 4330
91.5%
ValueCountFrequency (%)
1698343176 4
0.1%
1699173762 4
0.1%
1699196321 3
0.1%
1700067953 1
 
< 0.1%
1701776723 7
0.1%
1703096478 4
0.1%
1703320852 7
0.1%
1703404987 3
0.1%
1703852377 4
0.1%
1703934794 4
0.1%
ValueCountFrequency (%)
1730223050 4
 
0.1%
1730222572 5
 
0.1%
1730221645 22
0.5%
1730220087 23
0.5%
1730219902 3
 
0.1%
1730216598 22
0.5%
1730216403 5
 
0.1%
1730213788 6
 
0.1%
1730213660 15
0.3%
1730213247 4
 
0.1%
Distinct681
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size420.4 KiB
https://api.tvmaze.com/shows/78854
 
100
https://api.tvmaze.com/shows/73952
 
38
https://api.tvmaze.com/shows/73773
 
36
https://api.tvmaze.com/shows/72654
 
36
https://api.tvmaze.com/shows/73703
 
36
Other values (676)
4487 
ValueCountFrequency (%)
https://api.tvmaze.com/shows/78854 100
 
2.1%
https://api.tvmaze.com/shows/73952 38
 
0.8%
https://api.tvmaze.com/shows/73773 36
 
0.8%
https://api.tvmaze.com/shows/72654 36
 
0.8%
https://api.tvmaze.com/shows/73703 36
 
0.8%
https://api.tvmaze.com/shows/74045 34
 
0.7%
https://api.tvmaze.com/shows/42056 33
 
0.7%
https://api.tvmaze.com/shows/69806 32
 
0.7%
https://api.tvmaze.com/shows/73931 30
 
0.6%
https://api.tvmaze.com/shows/74100 28
 
0.6%
Other values (671) 4330
91.5%
ValueCountFrequency (%)
https 4733
100.0%
ValueCountFrequency (%)
api.tvmaze.com 4733
100.0%
ValueCountFrequency (%)
/shows/78854 100
 
2.1%
/shows/73952 38
 
0.8%
/shows/73773 36
 
0.8%
/shows/72654 36
 
0.8%
/shows/73703 36
 
0.8%
/shows/74045 34
 
0.7%
/shows/42056 33
 
0.7%
/shows/69806 32
 
0.7%
/shows/73931 30
 
0.6%
/shows/74100 28
 
0.6%
Other values (671) 4330
91.5%
ValueCountFrequency (%)
4733
100.0%
ValueCountFrequency (%)
4733
100.0%
Distinct681
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size443.8 KiB
https://api.tvmaze.com/episodes/2975897
 
100
https://api.tvmaze.com/episodes/2744151
 
38
https://api.tvmaze.com/episodes/2732738
 
36
https://api.tvmaze.com/episodes/2740225
 
36
https://api.tvmaze.com/episodes/2726108
 
36
Other values (676)
4487 
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/2975897 100
 
2.1%
https://api.tvmaze.com/episodes/2744151 38
 
0.8%
https://api.tvmaze.com/episodes/2732738 36
 
0.8%
https://api.tvmaze.com/episodes/2740225 36
 
0.8%
https://api.tvmaze.com/episodes/2726108 36
 
0.8%
https://api.tvmaze.com/episodes/2744350 34
 
0.7%
https://api.tvmaze.com/episodes/2755625 33
 
0.7%
https://api.tvmaze.com/episodes/2736579 32
 
0.7%
https://api.tvmaze.com/episodes/2739793 30
 
0.6%
https://api.tvmaze.com/episodes/2747891 28
 
0.6%
Other values (671) 4330
91.5%
ValueCountFrequency (%)
https 4733
100.0%
ValueCountFrequency (%)
api.tvmaze.com 4733
100.0%
ValueCountFrequency (%)
/episodes/2975897 100
 
2.1%
/episodes/2744151 38
 
0.8%
/episodes/2732738 36
 
0.8%
/episodes/2740225 36
 
0.8%
/episodes/2726108 36
 
0.8%
/episodes/2744350 34
 
0.7%
/episodes/2755625 33
 
0.7%
/episodes/2736579 32
 
0.7%
/episodes/2739793 30
 
0.6%
/episodes/2747891 28
 
0.6%
Other values (671) 4330
91.5%
ValueCountFrequency (%)
4733
100.0%
ValueCountFrequency (%)
4733
100.0%
Distinct519
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size376.9 KiB
2024-10-29T14:34:52.982569image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length116
Median length97
Mean length15.309106
Min length2

Characters and Unicode

Total characters72458
Distinct characters238
Distinct categories13 ?
Distinct scripts7 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)1.5%

Sample

1st rowСерия 10
2nd rowСерия 10
3rd rowСерия 10
4th rowСерия 10
5th rowСерия 10
ValueCountFrequency (%)
episode 2449
 
18.0%
the 400
 
2.9%
24 370
 
2.7%
36 193
 
1.4%
серия 180
 
1.3%
166
 
1.2%
8 142
 
1.0%
30 125
 
0.9%
of 125
 
0.9%
and 122
 
0.9%
Other values (1295) 9333
68.6%
2024-10-29T14:34:53.459953image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8872
 
12.2%
e 5780
 
8.0%
i 4448
 
6.1%
o 4445
 
6.1%
s 4104
 
5.7%
d 3440
 
4.7%
p 2921
 
4.0%
E 2768
 
3.8%
a 2706
 
3.7%
n 2090
 
2.9%
Other values (228) 30884
42.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 44662
61.6%
Uppercase Letter 9407
 
13.0%
Space Separator 8872
 
12.2%
Decimal Number 7357
 
10.2%
Other Punctuation 1273
 
1.8%
Other Letter 589
 
0.8%
Dash Punctuation 119
 
0.2%
Math Symbol 53
 
0.1%
Open Punctuation 39
 
0.1%
Close Punctuation 39
 
0.1%
Other values (3) 48
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5780
12.9%
i 4448
 
10.0%
o 4445
 
10.0%
s 4104
 
9.2%
d 3440
 
7.7%
p 2921
 
6.5%
a 2706
 
6.1%
n 2090
 
4.7%
t 1800
 
4.0%
r 1646
 
3.7%
Other values (90) 11282
25.3%
Uppercase Letter
ValueCountFrequency (%)
E 2768
29.4%
T 613
 
6.5%
S 428
 
4.5%
C 418
 
4.4%
A 398
 
4.2%
B 387
 
4.1%
P 382
 
4.1%
F 330
 
3.5%
D 311
 
3.3%
R 289
 
3.1%
Other values (50) 3083
32.8%
Other Letter
ValueCountFrequency (%)
ل 51
 
8.7%
48
 
8.1%
ا 29
 
4.9%
24
 
4.1%
24
 
4.1%
24
 
4.1%
24
 
4.1%
24
 
4.1%
24
 
4.1%
24
 
4.1%
Other values (29) 293
49.7%
Other Punctuation
ValueCountFrequency (%)
, 394
31.0%
. 231
18.1%
' 145
 
11.4%
/ 110
 
8.6%
: 97
 
7.6%
! 86
 
6.8%
? 58
 
4.6%
# 53
 
4.2%
& 38
 
3.0%
29
 
2.3%
Other values (3) 32
 
2.5%
Decimal Number
ValueCountFrequency (%)
2 1457
19.8%
1 1331
18.1%
0 959
13.0%
4 910
12.4%
3 889
12.1%
6 604
8.2%
9 347
 
4.7%
8 329
 
4.5%
7 286
 
3.9%
5 245
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 90
75.6%
23
 
19.3%
6
 
5.0%
Math Symbol
ValueCountFrequency (%)
| 39
73.6%
~ 12
 
22.6%
+ 2
 
3.8%
Open Punctuation
ValueCountFrequency (%)
( 38
97.4%
[ 1
 
2.6%
Close Punctuation
ValueCountFrequency (%)
) 38
97.4%
] 1
 
2.6%
Initial Punctuation
ValueCountFrequency (%)
19
65.5%
« 10
34.5%
Format
ValueCountFrequency (%)
6
66.7%
3
33.3%
Space Separator
ValueCountFrequency (%)
8872
100.0%
Final Punctuation
ValueCountFrequency (%)
» 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 49755
68.7%
Common 17800
 
24.6%
Cyrillic 4156
 
5.7%
Hangul 408
 
0.6%
Arabic 181
 
0.2%
Armenian 98
 
0.1%
Greek 60
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5780
 
11.6%
i 4448
 
8.9%
o 4445
 
8.9%
s 4104
 
8.2%
d 3440
 
6.9%
p 2921
 
5.9%
E 2768
 
5.6%
a 2706
 
5.4%
n 2090
 
4.2%
t 1800
 
3.6%
Other values (57) 15253
30.7%
Cyrillic
ValueCountFrequency (%)
е 404
 
9.7%
р 382
 
9.2%
а 372
 
9.0%
и 358
 
8.6%
я 273
 
6.6%
С 226
 
5.4%
н 179
 
4.3%
о 158
 
3.8%
т 132
 
3.2%
к 127
 
3.1%
Other values (52) 1545
37.2%
Common
ValueCountFrequency (%)
8872
49.8%
2 1457
 
8.2%
1 1331
 
7.5%
0 959
 
5.4%
4 910
 
5.1%
3 889
 
5.0%
6 604
 
3.4%
, 394
 
2.2%
9 347
 
1.9%
8 329
 
1.8%
Other values (29) 1708
 
9.6%
Arabic
ValueCountFrequency (%)
ل 51
28.2%
ا 29
16.0%
ة 24
13.3%
ق 24
13.3%
ح 23
12.7%
ي 4
 
2.2%
ه 3
 
1.7%
م 3
 
1.7%
ر 3
 
1.7%
س 3
 
1.7%
Other values (13) 14
 
7.7%
Greek
ValueCountFrequency (%)
α 8
13.3%
κ 6
 
10.0%
ο 4
 
6.7%
τ 4
 
6.7%
ώ 4
 
6.7%
γ 4
 
6.7%
ό 4
 
6.7%
ε 4
 
6.7%
ν 4
 
6.7%
έ 2
 
3.3%
Other values (8) 16
26.7%
Hangul
ValueCountFrequency (%)
48
 
11.8%
24
 
5.9%
24
 
5.9%
24
 
5.9%
24
 
5.9%
24
 
5.9%
24
 
5.9%
24
 
5.9%
24
 
5.9%
24
 
5.9%
Other values (6) 144
35.3%
Armenian
ValueCountFrequency (%)
մ 14
14.3%
ն 7
 
7.1%
ռ 7
 
7.1%
ծ 7
 
7.1%
ա 7
 
7.1%
ի 7
 
7.1%
ջ 7
 
7.1%
Է 7
 
7.1%
ը 7
 
7.1%
Ն 7
 
7.1%
Other values (3) 21
21.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67183
92.7%
Cyrillic 4156
 
5.7%
Hangul 408
 
0.6%
None 344
 
0.5%
Arabic 183
 
0.3%
Armenian 98
 
0.1%
Punctuation 86
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8872
 
13.2%
e 5780
 
8.6%
i 4448
 
6.6%
o 4445
 
6.6%
s 4104
 
6.1%
d 3440
 
5.1%
p 2921
 
4.3%
E 2768
 
4.1%
a 2706
 
4.0%
n 2090
 
3.1%
Other values (72) 25609
38.1%
Cyrillic
ValueCountFrequency (%)
е 404
 
9.7%
р 382
 
9.2%
а 372
 
9.0%
и 358
 
8.6%
я 273
 
6.6%
С 226
 
5.4%
н 179
 
4.3%
о 158
 
3.8%
т 132
 
3.2%
к 127
 
3.1%
Other values (52) 1545
37.2%
Arabic
ValueCountFrequency (%)
ل 51
27.9%
ا 29
15.8%
ة 24
13.1%
ق 24
13.1%
ح 23
12.6%
ي 4
 
2.2%
ه 3
 
1.6%
م 3
 
1.6%
ر 3
 
1.6%
س 3
 
1.6%
Other values (14) 16
 
8.7%
Hangul
ValueCountFrequency (%)
48
 
11.8%
24
 
5.9%
24
 
5.9%
24
 
5.9%
24
 
5.9%
24
 
5.9%
24
 
5.9%
24
 
5.9%
24
 
5.9%
24
 
5.9%
Other values (6) 144
35.3%
None
ValueCountFrequency (%)
å 38
 
11.0%
ä 37
 
10.8%
ö 36
 
10.5%
ü 32
 
9.3%
é 24
 
7.0%
ó 23
 
6.7%
á 20
 
5.8%
ø 15
 
4.4%
» 10
 
2.9%
« 10
 
2.9%
Other values (25) 99
28.8%
Punctuation
ValueCountFrequency (%)
29
33.7%
23
26.7%
19
22.1%
6
 
7.0%
6
 
7.0%
3
 
3.5%
Armenian
ValueCountFrequency (%)
մ 14
14.3%
ն 7
 
7.1%
ռ 7
 
7.1%
ծ 7
 
7.1%
ա 7
 
7.1%
ի 7
 
7.1%
ջ 7
 
7.1%
Է 7
 
7.1%
ը 7
 
7.1%
Ն 7
 
7.1%
Other values (3) 21
21.4%

_embedded_show_image
Unsupported

Missing  Rejected  Unsupported 

Missing4733
Missing (%)100.0%
Memory size37.1 KiB
Distinct67
Distinct (%)11.8%
Missing4165
Missing (%)88.0%
Memory size183.5 KiB
https://api.tvmaze.com/episodes/3020763
 
23
https://api.tvmaze.com/episodes/3034494
 
23
https://api.tvmaze.com/episodes/3024665
 
23
https://api.tvmaze.com/episodes/3016570
 
23
https://api.tvmaze.com/episodes/3034499
 
22
Other values (62)
454 
(Missing)
4165 
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/3020763 23
 
0.5%
https://api.tvmaze.com/episodes/3034494 23
 
0.5%
https://api.tvmaze.com/episodes/3024665 23
 
0.5%
https://api.tvmaze.com/episodes/3016570 23
 
0.5%
https://api.tvmaze.com/episodes/3034499 22
 
0.5%
https://api.tvmaze.com/episodes/3023091 22
 
0.5%
https://api.tvmaze.com/episodes/3034474 22
 
0.5%
https://api.tvmaze.com/episodes/3024688 22
 
0.5%
https://api.tvmaze.com/episodes/3038163 20
 
0.4%
https://api.tvmaze.com/episodes/3032264 19
 
0.4%
Other values (57) 349
 
7.4%
(Missing) 4165
88.0%
ValueCountFrequency (%)
https 568
 
12.0%
(Missing) 4165
88.0%
ValueCountFrequency (%)
api.tvmaze.com 568
 
12.0%
(Missing) 4165
88.0%
ValueCountFrequency (%)
/episodes/3034494 23
 
0.5%
/episodes/3024665 23
 
0.5%
/episodes/3016570 23
 
0.5%
/episodes/3020763 23
 
0.5%
/episodes/3034474 22
 
0.5%
/episodes/3034499 22
 
0.5%
/episodes/3023091 22
 
0.5%
/episodes/3024688 22
 
0.5%
/episodes/3038163 20
 
0.4%
/episodes/3032264 19
 
0.4%
Other values (57) 349
 
7.4%
(Missing) 4165
88.0%
ValueCountFrequency (%)
568
 
12.0%
(Missing) 4165
88.0%
ValueCountFrequency (%)
568
 
12.0%
(Missing) 4165
88.0%
Distinct61
Distinct (%)10.7%
Missing4165
Missing (%)88.0%
Memory size177.0 KiB
2024-10-29T14:34:53.719614image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length77
Median length59
Mean length17.339789
Min length3

Characters and Unicode

Total characters9849
Distinct characters90
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st rowEpisode 354
2nd rowEpisode 61
3rd row30/10/2024
4th row04/11/2024
5th row04/11/2024
ValueCountFrequency (%)
episode 236
 
14.2%
218 46
 
2.8%
tba 32
 
1.9%
2024 27
 
1.6%
episódio 23
 
1.4%
203 23
 
1.4%
ep 23
 
1.4%
14977 23
 
1.4%
emily 22
 
1.3%
stardom 22
 
1.3%
Other values (130) 1185
71.3%
2024-10-29T14:34:54.123406image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1094
 
11.1%
e 751
 
7.6%
o 602
 
6.1%
i 570
 
5.8%
s 477
 
4.8%
d 423
 
4.3%
a 362
 
3.7%
p 348
 
3.5%
E 334
 
3.4%
r 328
 
3.3%
Other values (80) 4560
46.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5735
58.2%
Decimal Number 1442
 
14.6%
Uppercase Letter 1208
 
12.3%
Space Separator 1094
 
11.1%
Other Punctuation 310
 
3.1%
Dash Punctuation 48
 
0.5%
Math Symbol 12
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 751
13.1%
o 602
10.5%
i 570
 
9.9%
s 477
 
8.3%
d 423
 
7.4%
a 362
 
6.3%
p 348
 
6.1%
r 328
 
5.7%
n 228
 
4.0%
t 215
 
3.7%
Other values (34) 1431
25.0%
Uppercase Letter
ValueCountFrequency (%)
E 334
27.6%
T 101
 
8.4%
W 76
 
6.3%
R 72
 
6.0%
S 71
 
5.9%
A 68
 
5.6%
D 56
 
4.6%
B 53
 
4.4%
O 51
 
4.2%
C 45
 
3.7%
Other values (15) 281
23.3%
Decimal Number
ValueCountFrequency (%)
1 297
20.6%
2 274
19.0%
0 219
15.2%
4 198
13.7%
3 134
9.3%
7 108
 
7.5%
8 105
 
7.3%
9 74
 
5.1%
6 20
 
1.4%
5 13
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 104
33.5%
/ 78
25.2%
. 73
23.5%
# 28
 
9.0%
: 10
 
3.2%
' 9
 
2.9%
! 8
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 37
77.1%
11
 
22.9%
Space Separator
ValueCountFrequency (%)
1094
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6508
66.1%
Common 2906
29.5%
Cyrillic 435
 
4.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 751
 
11.5%
o 602
 
9.3%
i 570
 
8.8%
s 477
 
7.3%
d 423
 
6.5%
a 362
 
5.6%
p 348
 
5.3%
E 334
 
5.1%
r 328
 
5.0%
n 228
 
3.5%
Other values (38) 2085
32.0%
Common
ValueCountFrequency (%)
1094
37.6%
1 297
 
10.2%
2 274
 
9.4%
0 219
 
7.5%
4 198
 
6.8%
3 134
 
4.6%
7 108
 
3.7%
8 105
 
3.6%
, 104
 
3.6%
/ 78
 
2.7%
Other values (11) 295
 
10.2%
Cyrillic
ValueCountFrequency (%)
я 45
10.3%
о 45
10.3%
л 40
 
9.2%
и 40
 
9.2%
к 35
 
8.0%
е 30
 
6.9%
б 30
 
6.9%
н 25
 
5.7%
д 20
 
4.6%
т 15
 
3.4%
Other values (11) 110
25.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9368
95.1%
Cyrillic 435
 
4.4%
None 35
 
0.4%
Punctuation 11
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1094
 
11.7%
e 751
 
8.0%
o 602
 
6.4%
i 570
 
6.1%
s 477
 
5.1%
d 423
 
4.5%
a 362
 
3.9%
p 348
 
3.7%
E 334
 
3.6%
r 328
 
3.5%
Other values (56) 4079
43.5%
Cyrillic
ValueCountFrequency (%)
я 45
10.3%
о 45
10.3%
л 40
 
9.2%
и 40
 
9.2%
к 35
 
8.0%
е 30
 
6.9%
б 30
 
6.9%
н 25
 
5.7%
д 20
 
4.6%
т 15
 
3.4%
Other values (11) 110
25.3%
None
ValueCountFrequency (%)
ó 23
65.7%
é 12
34.3%
Punctuation
ValueCountFrequency (%)
11
100.0%

image_medium
URL

Missing 

Distinct1216
Distinct (%)100.0%
Missing3517
Missing (%)74.3%
Memory size264.4 KiB
https://static.tvmaze.com/uploads/images/medium_landscape/501/1254514.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/517/1294550.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/517/1294549.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/517/1294546.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/504/1261938.jpg
 
1
Other values (1211)
1211 
(Missing)
3517 
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/501/1254514.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/medium_landscape/517/1294550.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/medium_landscape/517/1294549.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/medium_landscape/517/1294546.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/medium_landscape/504/1261938.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/medium_landscape/500/1251867.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/medium_landscape/537/1343978.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/medium_landscape/500/1252011.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/medium_landscape/500/1252198.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/medium_landscape/500/1250578.jpg 1
 
< 0.1%
Other values (1206) 1206
 
25.5%
(Missing) 3517
74.3%
ValueCountFrequency (%)
https 1216
 
25.7%
(Missing) 3517
74.3%
ValueCountFrequency (%)
static.tvmaze.com 1216
 
25.7%
(Missing) 3517
74.3%
ValueCountFrequency (%)
/uploads/images/medium_landscape/495/1238394.jpg 1
 
< 0.1%
/uploads/images/medium_landscape/501/1254514.jpg 1
 
< 0.1%
/uploads/images/medium_landscape/517/1294550.jpg 1
 
< 0.1%
/uploads/images/medium_landscape/517/1294549.jpg 1
 
< 0.1%
/uploads/images/medium_landscape/517/1294546.jpg 1
 
< 0.1%
/uploads/images/medium_landscape/504/1261938.jpg 1
 
< 0.1%
/uploads/images/medium_landscape/500/1251867.jpg 1
 
< 0.1%
/uploads/images/medium_landscape/537/1343978.jpg 1
 
< 0.1%
/uploads/images/medium_landscape/500/1252011.jpg 1
 
< 0.1%
/uploads/images/medium_landscape/500/1252198.jpg 1
 
< 0.1%
Other values (1206) 1206
 
25.5%
(Missing) 3517
74.3%
ValueCountFrequency (%)
1216
 
25.7%
(Missing) 3517
74.3%
ValueCountFrequency (%)
1216
 
25.7%
(Missing) 3517
74.3%

image_original
URL

Missing 

Distinct1216
Distinct (%)100.0%
Missing3517
Missing (%)74.3%
Memory size266.8 KiB
https://static.tvmaze.com/uploads/images/original_untouched/501/1254514.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/517/1294550.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/517/1294549.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/517/1294546.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/504/1261938.jpg
 
1
Other values (1211)
1211 
(Missing)
3517 
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/501/1254514.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/original_untouched/517/1294550.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/original_untouched/517/1294549.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/original_untouched/517/1294546.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/original_untouched/504/1261938.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/original_untouched/500/1251867.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/original_untouched/537/1343978.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/original_untouched/500/1252011.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/original_untouched/500/1252198.jpg 1
 
< 0.1%
https://static.tvmaze.com/uploads/images/original_untouched/500/1250578.jpg 1
 
< 0.1%
Other values (1206) 1206
 
25.5%
(Missing) 3517
74.3%
ValueCountFrequency (%)
https 1216
 
25.7%
(Missing) 3517
74.3%
ValueCountFrequency (%)
static.tvmaze.com 1216
 
25.7%
(Missing) 3517
74.3%
ValueCountFrequency (%)
/uploads/images/original_untouched/495/1238394.jpg 1
 
< 0.1%
/uploads/images/original_untouched/501/1254514.jpg 1
 
< 0.1%
/uploads/images/original_untouched/517/1294550.jpg 1
 
< 0.1%
/uploads/images/original_untouched/517/1294549.jpg 1
 
< 0.1%
/uploads/images/original_untouched/517/1294546.jpg 1
 
< 0.1%
/uploads/images/original_untouched/504/1261938.jpg 1
 
< 0.1%
/uploads/images/original_untouched/500/1251867.jpg 1
 
< 0.1%
/uploads/images/original_untouched/537/1343978.jpg 1
 
< 0.1%
/uploads/images/original_untouched/500/1252011.jpg 1
 
< 0.1%
/uploads/images/original_untouched/500/1252198.jpg 1
 
< 0.1%
Other values (1206) 1206
 
25.5%
(Missing) 3517
74.3%
ValueCountFrequency (%)
1216
 
25.7%
(Missing) 3517
74.3%
ValueCountFrequency (%)
1216
 
25.7%
(Missing) 3517
74.3%

_embedded_show_network_id
Real number (ℝ)

High correlation  Missing 

Distinct40
Distinct (%)7.8%
Missing4217
Missing (%)89.1%
Infinite0
Infinite (%)0.0%
Mean570.05039
Minimum1
Maximum1963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-10-29T14:34:54.248987image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q1166
median308
Q31039
95-th percentile1963
Maximum1963
Range1962
Interquartile range (IQR)873

Descriptive statistics

Standard deviation572.20746
Coefficient of variation (CV)1.003784
Kurtosis0.018955377
Mean570.05039
Median Absolute Deviation (MAD)232
Skewness1.0663366
Sum294146
Variance327421.38
MonotonicityNot monotonic
2024-10-29T14:34:54.374312image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
481 45
 
1.0%
1282 41
 
0.9%
1 39
 
0.8%
276 36
 
0.8%
297 28
 
0.6%
1039 28
 
0.6%
1963 28
 
0.6%
166 24
 
0.5%
514 23
 
0.5%
185 22
 
0.5%
Other values (30) 202
 
4.3%
(Missing) 4217
89.1%
ValueCountFrequency (%)
1 39
0.8%
2 4
 
0.1%
3 22
0.5%
5 5
 
0.1%
29 10
 
0.2%
30 5
 
0.1%
40 4
 
0.1%
42 3
 
0.1%
52 3
 
0.1%
76 4
 
0.1%
ValueCountFrequency (%)
1963 28
0.6%
1766 4
 
0.1%
1683 15
 
0.3%
1501 1
 
< 0.1%
1328 9
 
0.2%
1282 41
0.9%
1058 15
 
0.3%
1039 28
0.6%
790 15
 
0.3%
758 4
 
0.1%

_embedded_show_network_name
Categorical

High correlation  Missing 

Distinct39
Distinct (%)7.6%
Missing4217
Missing (%)89.1%
Memory size298.6 KiB
Beijing TV
45 
CCTV-1
41 
NBC
39 
Hunan TV
36 
CCTV-8
 
28
Other values (34)
327 

Length

Max length21
Median length20
Mean length7.4282946
Min length3

Characters and Unicode

Total characters3833
Distinct characters63
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st rowMBC
2nd rowBeijing TV
3rd rowBeijing TV
4th rowtvN
5th rowCCTV-1

Common Values

ValueCountFrequency (%)
Beijing TV 45
 
1.0%
CCTV-1 41
 
0.9%
NBC 39
 
0.8%
Hunan TV 36
 
0.8%
CCTV-8 28
 
0.6%
Disney Junior 28
 
0.6%
Shaanxi Satellite TV 28
 
0.6%
MBC 24
 
0.5%
ABC 23
 
0.5%
ТВ-3 23
 
0.5%
Other values (29) 201
 
4.2%
(Missing) 4217
89.1%

Length

2024-10-29T14:34:54.504467image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tv 122
 
15.4%
beijing 45
 
5.7%
cctv-1 41
 
5.2%
nbc 39
 
4.9%
hunan 36
 
4.6%
cctv-8 28
 
3.5%
disney 28
 
3.5%
junior 28
 
3.5%
shaanxi 28
 
3.5%
satellite 28
 
3.5%
Other values (42) 367
46.5%

Most occurring characters

ValueCountFrequency (%)
C 280
 
7.3%
274
 
7.1%
n 262
 
6.8%
T 246
 
6.4%
i 224
 
5.8%
V 207
 
5.4%
e 204
 
5.3%
a 191
 
5.0%
B 151
 
3.9%
N 114
 
3.0%
Other values (53) 1680
43.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1833
47.8%
Uppercase Letter 1502
39.2%
Space Separator 274
 
7.1%
Decimal Number 115
 
3.0%
Dash Punctuation 99
 
2.6%
Other Punctuation 10
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 262
14.3%
i 224
12.2%
e 204
11.1%
a 191
 
10.4%
o 109
 
5.9%
l 97
 
5.3%
t 85
 
4.6%
u 64
 
3.5%
h 58
 
3.2%
s 54
 
2.9%
Other values (21) 485
26.5%
Uppercase Letter
ValueCountFrequency (%)
C 280
18.6%
T 246
16.4%
V 207
13.8%
B 151
10.1%
N 114
7.6%
S 80
 
5.3%
Т 61
 
4.1%
M 48
 
3.2%
D 48
 
3.2%
A 46
 
3.1%
Other values (15) 221
14.7%
Decimal Number
ValueCountFrequency (%)
1 45
39.1%
3 38
33.0%
8 28
24.3%
2 4
 
3.5%
Space Separator
ValueCountFrequency (%)
274
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%
Other Punctuation
ValueCountFrequency (%)
& 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3082
80.4%
Common 498
 
13.0%
Cyrillic 253
 
6.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 280
 
9.1%
n 262
 
8.5%
T 246
 
8.0%
i 224
 
7.3%
V 207
 
6.7%
e 204
 
6.6%
a 191
 
6.2%
B 151
 
4.9%
N 114
 
3.7%
o 109
 
3.5%
Other values (34) 1094
35.5%
Cyrillic
ValueCountFrequency (%)
Т 61
24.1%
а 30
11.9%
В 23
 
9.1%
Н 19
 
7.5%
н 15
 
5.9%
т 15
 
5.9%
л 15
 
5.9%
я 15
 
5.9%
П 15
 
5.9%
к 15
 
5.9%
Other values (2) 30
11.9%
Common
ValueCountFrequency (%)
274
55.0%
- 99
 
19.9%
1 45
 
9.0%
3 38
 
7.6%
8 28
 
5.6%
& 10
 
2.0%
2 4
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3574
93.2%
Cyrillic 253
 
6.6%
None 6
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 280
 
7.8%
274
 
7.7%
n 262
 
7.3%
T 246
 
6.9%
i 224
 
6.3%
V 207
 
5.8%
e 204
 
5.7%
a 191
 
5.3%
B 151
 
4.2%
N 114
 
3.2%
Other values (40) 1421
39.8%
Cyrillic
ValueCountFrequency (%)
Т 61
24.1%
а 30
11.9%
В 23
 
9.1%
Н 19
 
7.5%
н 15
 
5.9%
т 15
 
5.9%
л 15
 
5.9%
я 15
 
5.9%
П 15
 
5.9%
к 15
 
5.9%
Other values (2) 30
11.9%
None
ValueCountFrequency (%)
é 6
100.0%

_embedded_show_network_country_name
Categorical

High correlation  Missing 

Distinct13
Distinct (%)2.5%
Missing4217
Missing (%)89.1%
Memory size297.6 KiB
China
178 
United States
160 
Russian Federation
57 
Korea, Republic of
43 
Denmark
21 
Other values (8)
57 

Length

Max length18
Median length14
Mean length10.352713
Min length5

Characters and Unicode

Total characters5342
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowKorea, Republic of
2nd rowChina
3rd rowChina
4th rowKorea, Republic of
5th rowChina

Common Values

ValueCountFrequency (%)
China 178
 
3.8%
United States 160
 
3.4%
Russian Federation 57
 
1.2%
Korea, Republic of 43
 
0.9%
Denmark 21
 
0.4%
Egypt 15
 
0.3%
Japan 12
 
0.3%
Hungary 11
 
0.2%
Czech Republic 9
 
0.2%
Saudi Arabia 4
 
0.1%
Other values (3) 6
 
0.1%
(Missing) 4217
89.1%

Length

2024-10-29T14:34:54.617753image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
china 178
21.4%
united 160
19.2%
states 160
19.2%
russian 57
 
6.9%
federation 57
 
6.9%
republic 52
 
6.2%
korea 43
 
5.2%
of 43
 
5.2%
denmark 21
 
2.5%
egypt 15
 
1.8%
Other values (8) 46
 
5.5%

Most occurring characters

ValueCountFrequency (%)
a 576
 
10.8%
e 561
 
10.5%
t 553
 
10.4%
i 513
 
9.6%
n 501
 
9.4%
316
 
5.9%
s 275
 
5.1%
d 224
 
4.2%
C 190
 
3.6%
h 187
 
3.5%
Other values (24) 1446
27.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4194
78.5%
Uppercase Letter 789
 
14.8%
Space Separator 316
 
5.9%
Other Punctuation 43
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 576
13.7%
e 561
13.4%
t 553
13.2%
i 513
12.2%
n 501
11.9%
s 275
6.6%
d 224
 
5.3%
h 187
 
4.5%
o 143
 
3.4%
r 139
 
3.3%
Other values (11) 522
12.4%
Uppercase Letter
ValueCountFrequency (%)
C 190
24.1%
S 164
20.8%
U 160
20.3%
R 109
13.8%
F 59
 
7.5%
K 43
 
5.4%
D 21
 
2.7%
E 15
 
1.9%
J 12
 
1.5%
H 11
 
1.4%
Space Separator
ValueCountFrequency (%)
316
100.0%
Other Punctuation
ValueCountFrequency (%)
, 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4983
93.3%
Common 359
 
6.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 576
11.6%
e 561
11.3%
t 553
11.1%
i 513
10.3%
n 501
10.1%
s 275
 
5.5%
d 224
 
4.5%
C 190
 
3.8%
h 187
 
3.8%
S 164
 
3.3%
Other values (22) 1239
24.9%
Common
ValueCountFrequency (%)
316
88.0%
, 43
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5342
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 576
 
10.8%
e 561
 
10.5%
t 553
 
10.4%
i 513
 
9.6%
n 501
 
9.4%
316
 
5.9%
s 275
 
5.1%
d 224
 
4.2%
C 190
 
3.6%
h 187
 
3.5%
Other values (24) 1446
27.1%

_embedded_show_network_country_code
Categorical

High correlation  Missing 

Distinct13
Distinct (%)2.5%
Missing4217
Missing (%)89.1%
Memory size293.4 KiB
CN
178 
US
160 
RU
57 
KR
43 
DK
21 
Other values (8)
57 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters1032
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowKR
2nd rowCN
3rd rowCN
4th rowKR
5th rowCN

Common Values

ValueCountFrequency (%)
CN 178
 
3.8%
US 160
 
3.4%
RU 57
 
1.2%
KR 43
 
0.9%
DK 21
 
0.4%
EG 15
 
0.3%
JP 12
 
0.3%
HU 11
 
0.2%
CZ 9
 
0.2%
SA 4
 
0.1%
Other values (3) 6
 
0.1%
(Missing) 4217
89.1%

Length

2024-10-29T14:34:54.720347image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cn 178
34.5%
us 160
31.0%
ru 57
 
11.0%
kr 43
 
8.3%
dk 21
 
4.1%
eg 15
 
2.9%
jp 12
 
2.3%
hu 11
 
2.1%
cz 9
 
1.7%
sa 4
 
0.8%
Other values (3) 6
 
1.2%

Most occurring characters

ValueCountFrequency (%)
U 229
22.2%
C 190
18.4%
N 178
17.2%
S 164
15.9%
R 102
9.9%
K 64
 
6.2%
D 21
 
2.0%
E 15
 
1.5%
G 15
 
1.5%
J 12
 
1.2%
Other values (5) 42
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1032
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 229
22.2%
C 190
18.4%
N 178
17.2%
S 164
15.9%
R 102
9.9%
K 64
 
6.2%
D 21
 
2.0%
E 15
 
1.5%
G 15
 
1.5%
J 12
 
1.2%
Other values (5) 42
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 1032
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 229
22.2%
C 190
18.4%
N 178
17.2%
S 164
15.9%
R 102
9.9%
K 64
 
6.2%
D 21
 
2.0%
E 15
 
1.5%
G 15
 
1.5%
J 12
 
1.2%
Other values (5) 42
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1032
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 229
22.2%
C 190
18.4%
N 178
17.2%
S 164
15.9%
R 102
9.9%
K 64
 
6.2%
D 21
 
2.0%
E 15
 
1.5%
G 15
 
1.5%
J 12
 
1.2%
Other values (5) 42
 
4.1%

_embedded_show_network_country_timezone
Categorical

High correlation  Missing 

Distinct13
Distinct (%)2.5%
Missing4217
Missing (%)89.1%
Memory size299.4 KiB
Asia/Shanghai
178 
America/New_York
160 
Asia/Kamchatka
57 
Asia/Seoul
43 
Europe/Copenhagen
21 
Other values (8)
57 

Length

Max length17
Median length16
Mean length13.895349
Min length10

Characters and Unicode

Total characters7170
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowAsia/Seoul
2nd rowAsia/Shanghai
3rd rowAsia/Shanghai
4th rowAsia/Seoul
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Asia/Shanghai 178
 
3.8%
America/New_York 160
 
3.4%
Asia/Kamchatka 57
 
1.2%
Asia/Seoul 43
 
0.9%
Europe/Copenhagen 21
 
0.4%
Africa/Cairo 15
 
0.3%
Asia/Tokyo 12
 
0.3%
Europe/Budapest 11
 
0.2%
Europe/Prague 9
 
0.2%
Asia/Riyadh 4
 
0.1%
Other values (3) 6
 
0.1%
(Missing) 4217
89.1%

Length

2024-10-29T14:34:54.834551image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asia/shanghai 178
34.5%
america/new_york 160
31.0%
asia/kamchatka 57
 
11.0%
asia/seoul 43
 
8.3%
europe/copenhagen 21
 
4.1%
africa/cairo 15
 
2.9%
asia/tokyo 12
 
2.3%
europe/budapest 11
 
2.1%
europe/prague 9
 
1.7%
asia/riyadh 4
 
0.8%
Other values (3) 6
 
1.2%

Most occurring characters

ValueCountFrequency (%)
a 1069
14.9%
i 675
 
9.4%
/ 516
 
7.2%
A 473
 
6.6%
e 472
 
6.6%
h 438
 
6.1%
r 408
 
5.7%
s 308
 
4.3%
o 306
 
4.3%
c 235
 
3.3%
Other values (25) 2270
31.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5302
73.9%
Uppercase Letter 1192
 
16.6%
Other Punctuation 516
 
7.2%
Connector Punctuation 160
 
2.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1069
20.2%
i 675
12.7%
e 472
8.9%
h 438
8.3%
r 408
 
7.7%
s 308
 
5.8%
o 306
 
5.8%
c 235
 
4.4%
k 229
 
4.3%
n 221
 
4.2%
Other values (11) 941
17.7%
Uppercase Letter
ValueCountFrequency (%)
A 473
39.7%
S 222
18.6%
N 160
 
13.4%
Y 160
 
13.4%
K 57
 
4.8%
E 43
 
3.6%
C 36
 
3.0%
T 12
 
1.0%
B 11
 
0.9%
P 11
 
0.9%
Other values (2) 7
 
0.6%
Other Punctuation
ValueCountFrequency (%)
/ 516
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 160
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6494
90.6%
Common 676
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1069
16.5%
i 675
 
10.4%
A 473
 
7.3%
e 472
 
7.3%
h 438
 
6.7%
r 408
 
6.3%
s 308
 
4.7%
o 306
 
4.7%
c 235
 
3.6%
k 229
 
3.5%
Other values (23) 1881
29.0%
Common
ValueCountFrequency (%)
/ 516
76.3%
_ 160
 
23.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1069
14.9%
i 675
 
9.4%
/ 516
 
7.2%
A 473
 
6.6%
e 472
 
6.6%
h 438
 
6.1%
r 408
 
5.7%
s 308
 
4.3%
o 306
 
4.3%
c 235
 
3.3%
Other values (25) 2270
31.7%

_embedded_show_network_officialSite
Categorical

High correlation  Missing 

Distinct14
Distinct (%)8.9%
Missing4575
Missing (%)96.7%
Memory size298.0 KiB
https://www.nbc.com/
39 
https://tv3.ru/
23 
https://abc.com/
22 
https://www.foxnews.com/
22 
https://www.5-tv.ru/
15 
Other values (9)
37 

Length

Max length38
Median length32
Mean length20.025316
Min length15

Characters and Unicode

Total characters3164
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st rowhttps://www.usanetwork.com
2nd rowhttps://www.nbc.com/
3rd rowhttps://abc.com/
4th rowhttps://tv.nova.cz/
5th rowhttps://www.cwtv.com/

Common Values

ValueCountFrequency (%)
https://www.nbc.com/ 39
 
0.8%
https://tv3.ru/ 23
 
0.5%
https://abc.com/ 22
 
0.5%
https://www.foxnews.com/ 22
 
0.5%
https://www.5-tv.ru/ 15
 
0.3%
https://tv.nova.cz/ 9
 
0.2%
https://www.usanetwork.com 5
 
0.1%
https://www.cwtv.com/ 5
 
0.1%
https://www.tbn.org/ 4
 
0.1%
https://www.cbs.com/ 4
 
0.1%
Other values (4) 10
 
0.2%
(Missing) 4575
96.7%

Length

2024-10-29T14:34:54.955117image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.nbc.com 39
24.7%
https://tv3.ru 23
14.6%
https://abc.com 22
13.9%
https://www.foxnews.com 22
13.9%
https://www.5-tv.ru 15
 
9.5%
https://tv.nova.cz 9
 
5.7%
https://www.usanetwork.com 5
 
3.2%
https://www.cwtv.com 5
 
3.2%
https://www.tbn.org 4
 
2.5%
https://www.cbs.com 4
 
2.5%
Other values (4) 10
 
6.3%

Most occurring characters

ValueCountFrequency (%)
/ 472
14.9%
t 387
12.2%
w 335
10.6%
. 272
8.6%
s 192
 
6.1%
c 192
 
6.1%
p 164
 
5.2%
h 161
 
5.1%
: 158
 
5.0%
o 152
 
4.8%
Other values (19) 679
21.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2206
69.7%
Other Punctuation 902
28.5%
Decimal Number 38
 
1.2%
Dash Punctuation 18
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 387
17.5%
w 335
15.2%
s 192
8.7%
c 192
8.7%
p 164
7.4%
h 161
7.3%
o 152
 
6.9%
m 100
 
4.5%
n 89
 
4.0%
b 73
 
3.3%
Other values (13) 361
16.4%
Other Punctuation
ValueCountFrequency (%)
/ 472
52.3%
. 272
30.2%
: 158
 
17.5%
Decimal Number
ValueCountFrequency (%)
3 23
60.5%
5 15
39.5%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2206
69.7%
Common 958
30.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 387
17.5%
w 335
15.2%
s 192
8.7%
c 192
8.7%
p 164
7.4%
h 161
7.3%
o 152
 
6.9%
m 100
 
4.5%
n 89
 
4.0%
b 73
 
3.3%
Other values (13) 361
16.4%
Common
ValueCountFrequency (%)
/ 472
49.3%
. 272
28.4%
: 158
 
16.5%
3 23
 
2.4%
- 18
 
1.9%
5 15
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3164
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 472
14.9%
t 387
12.2%
w 335
10.6%
. 272
8.6%
s 192
 
6.1%
c 192
 
6.1%
p 164
 
5.2%
h 161
 
5.1%
: 158
 
5.0%
o 152
 
4.8%
Other values (19) 679
21.5%

_embedded_show_webChannel
Unsupported

Missing  Rejected  Unsupported 

Missing4733
Missing (%)100.0%
Memory size37.1 KiB

_embedded_show_webChannel_country
Unsupported

Missing  Rejected  Unsupported 

Missing4733
Missing (%)100.0%
Memory size37.1 KiB
Distinct2
Distinct (%)50.0%
Missing4729
Missing (%)99.9%
Memory size148.2 KiB
2024-10-29T14:34:55.063679image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length18
Median length7
Mean length9.75
Min length7

Characters and Unicode

Total characters39
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st rowUkraine
2nd rowUkraine
3rd rowRussian Federation
4th rowUkraine
ValueCountFrequency (%)
ukraine 3
60.0%
russian 1
 
20.0%
federation 1
 
20.0%
2024-10-29T14:34:55.391779image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5
12.8%
i 5
12.8%
n 5
12.8%
e 5
12.8%
r 4
10.3%
U 3
7.7%
k 3
7.7%
s 2
 
5.1%
R 1
 
2.6%
u 1
 
2.6%
Other values (5) 5
12.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 33
84.6%
Uppercase Letter 5
 
12.8%
Space Separator 1
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 5
15.2%
i 5
15.2%
n 5
15.2%
e 5
15.2%
r 4
12.1%
k 3
9.1%
s 2
 
6.1%
u 1
 
3.0%
d 1
 
3.0%
t 1
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
U 3
60.0%
R 1
 
20.0%
F 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38
97.4%
Common 1
 
2.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 5
13.2%
i 5
13.2%
n 5
13.2%
e 5
13.2%
r 4
10.5%
U 3
7.9%
k 3
7.9%
s 2
 
5.3%
R 1
 
2.6%
u 1
 
2.6%
Other values (4) 4
10.5%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 5
12.8%
i 5
12.8%
n 5
12.8%
e 5
12.8%
r 4
10.3%
U 3
7.7%
k 3
7.7%
s 2
 
5.1%
R 1
 
2.6%
u 1
 
2.6%
Other values (5) 5
12.8%
Distinct2
Distinct (%)50.0%
Missing4729
Missing (%)99.9%
Memory size148.1 KiB
2024-10-29T14:34:55.451948image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters8
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st rowUA
2nd rowUA
3rd rowRU
4th rowUA
ValueCountFrequency (%)
ua 3
75.0%
ru 1
 
25.0%
2024-10-29T14:34:55.605523image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 4
50.0%
A 3
37.5%
R 1
 
12.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 8
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U 4
50.0%
A 3
37.5%
R 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 8
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 4
50.0%
A 3
37.5%
R 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 4
50.0%
A 3
37.5%
R 1
 
12.5%
Distinct2
Distinct (%)50.0%
Missing4729
Missing (%)99.9%
Memory size148.2 KiB
2024-10-29T14:34:55.719867image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length11.75
Min length11

Characters and Unicode

Total characters47
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st rowEurope/Kyiv
2nd rowEurope/Kyiv
3rd rowAsia/Kamchatka
4th rowEurope/Kyiv
ValueCountFrequency (%)
europe/kyiv 3
75.0%
asia/kamchatka 1
 
25.0%
2024-10-29T14:34:55.951525image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 4
 
8.5%
K 4
 
8.5%
a 4
 
8.5%
/ 4
 
8.5%
v 3
 
6.4%
u 3
 
6.4%
y 3
 
6.4%
E 3
 
6.4%
e 3
 
6.4%
p 3
 
6.4%
Other values (9) 13
27.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 35
74.5%
Uppercase Letter 8
 
17.0%
Other Punctuation 4
 
8.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 4
11.4%
a 4
11.4%
v 3
8.6%
u 3
8.6%
y 3
8.6%
e 3
8.6%
p 3
8.6%
o 3
8.6%
r 3
8.6%
s 1
 
2.9%
Other values (5) 5
14.3%
Uppercase Letter
ValueCountFrequency (%)
K 4
50.0%
E 3
37.5%
A 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 43
91.5%
Common 4
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 4
 
9.3%
K 4
 
9.3%
a 4
 
9.3%
v 3
 
7.0%
u 3
 
7.0%
y 3
 
7.0%
E 3
 
7.0%
e 3
 
7.0%
p 3
 
7.0%
o 3
 
7.0%
Other values (8) 10
23.3%
Common
ValueCountFrequency (%)
/ 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 4
 
8.5%
K 4
 
8.5%
a 4
 
8.5%
/ 4
 
8.5%
v 3
 
6.4%
u 3
 
6.4%
y 3
 
6.4%
E 3
 
6.4%
e 3
 
6.4%
p 3
 
6.4%
Other values (9) 13
27.7%

Interactions

2024-10-29T14:34:38.964804image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:19.786772image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:21.195118image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:22.566802image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:23.874500image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:25.667540image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:26.955683image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:28.429884image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:29.833613image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:31.158790image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:32.440851image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:33.728473image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:35.131308image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:36.280940image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:37.633065image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:39.048568image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:19.880802image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:21.286776image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:22.651629image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:23.962095image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:25.765225image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:27.057402image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:28.517543image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:29.924902image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:31.242332image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:32.527459image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:33.815614image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:35.207958image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:36.370561image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:37.725201image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:39.138999image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:20.049059image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:21.381886image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:22.744655image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:24.053933image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:25.857340image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:27.164421image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:28.611213image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:30.018523image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:31.335927image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:32.617556image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:33.908457image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:35.290573image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:36.467288image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:37.817648image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:39.219789image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:20.129977image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:21.467996image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:22.824016image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:24.146126image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:25.949115image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:27.255716image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:28.696368image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:30.102314image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:31.428878image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:32.701829image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:33.989374image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:35.367565image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:36.555300image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:37.903270image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:39.304917image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:20.216586image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:21.557631image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:22.909365image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:24.236651image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:26.030434image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:27.354535image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:28.781043image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:30.186609image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:31.512903image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:32.785881image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:34.075205image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:35.444891image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:36.641395image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:37.990625image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:39.375623image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:20.306702image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:21.645964image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:22.996018image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:24.317733image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:26.111999image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:27.460806image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:28.861181image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:30.274400image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:31.590383image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:32.865805image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:34.157514image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:35.521579image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:36.731477image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:38.075558image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:39.569371image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:20.401483image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:21.742788image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:23.092472image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:24.432188image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:26.200172image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:27.568443image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:28.956339image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:30.370662image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:31.682803image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:32.958578image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:34.252230image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:35.604241image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:36.828452image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:38.170972image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:39.652839image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:20.491699image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:21.835655image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:23.177647image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:24.532669image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:26.285829image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:27.670646image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:29.044507image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:30.457472image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:31.757181image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:33.044791image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:34.341772image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:35.677291image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:36.917454image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:38.259901image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:39.742708image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:20.579857image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:21.927663image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:23.263939image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:24.764098image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:26.380039image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:27.769325image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:29.131673image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:30.547284image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:31.843124image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:33.131205image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:34.429769image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:35.755570image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:37.005384image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:38.349377image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:39.823354image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:20.668175image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:22.023174image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:23.358210image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:24.914003image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:26.459962image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:27.864845image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:29.211325image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:30.636338image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:31.931985image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:33.218774image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:34.617022image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:35.839862image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:37.099629image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:38.441752image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:39.905571image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:20.754130image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:22.111267image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:23.443365image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:25.095816image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:26.535645image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:27.957650image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:29.295980image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:30.722698image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:32.013649image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:33.295793image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:34.701460image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:35.918776image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:37.185674image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:38.527655image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:39.994083image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:20.845830image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:22.202647image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:23.530087image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:25.220613image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:26.617236image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:28.052834image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:29.382775image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:30.808969image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:32.095933image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:33.382859image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:34.785632image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:35.992908image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:37.280808image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:38.615865image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:40.066945image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:20.923036image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:22.279212image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:23.605112image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:25.331711image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:26.695892image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:28.133481image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:29.459427image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:30.884650image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:32.181951image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:33.457529image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:34.857305image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:36.059683image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:37.352116image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:38.691881image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:40.159065image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:21.013681image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:22.377383image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:23.696446image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:25.442517image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:26.790587image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:28.232997image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:29.554526image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:30.975773image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:32.274578image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:33.549047image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:34.950665image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:36.132758image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:37.445476image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:38.787485image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:40.247084image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:21.108607image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:22.473629image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:23.787419image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:25.553844image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:26.874839image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:28.331209image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:29.748925image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:31.068816image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:32.365165image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:33.636010image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:35.041815image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:36.209389image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:37.539678image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-10-29T14:34:38.875783image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-10-29T14:34:56.049296image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
_embedded_show_averageRuntime_embedded_show_externals_thetvdb_embedded_show_externals_tvrage_embedded_show_id_embedded_show_language_embedded_show_network_country_code_embedded_show_network_country_name_embedded_show_network_country_timezone_embedded_show_network_id_embedded_show_network_name_embedded_show_network_officialSite_embedded_show_rating_average_embedded_show_runtime_embedded_show_schedule_time_embedded_show_status_embedded_show_type_embedded_show_updated_embedded_show_webChannel_country_code_embedded_show_webChannel_country_name_embedded_show_webChannel_country_timezone_embedded_show_webChannel_id_embedded_show_weightairdateidnumberrating_averageruntimeseasontype
_embedded_show_averageRuntime1.000-0.2180.463-0.0320.2450.5510.5510.551-0.4410.7890.9500.0810.9900.4830.2140.2840.1250.3470.3470.3470.2620.1050.0690.014-0.1840.3390.9710.3910.000
_embedded_show_externals_thetvdb-0.2181.0000.8700.8720.3910.6000.6000.6000.1570.9070.857-0.173-0.2310.5230.3540.251-0.4020.3000.3000.3000.005-0.5900.0770.156-0.0010.002-0.173-0.7910.088
_embedded_show_externals_tvrage0.4630.8701.0000.0440.7270.7210.7210.721-0.7140.9861.000-0.2620.1230.4850.6540.597-0.2200.7580.7580.7580.221-0.0130.282-0.140-0.126-0.2090.531-0.3890.000
_embedded_show_id-0.0320.8720.0441.0000.2740.5320.5320.5320.1380.8390.896-0.1850.2890.4170.2880.228-0.1550.3440.3440.3440.231-0.7080.0910.4500.0670.158-0.003-0.3500.056
_embedded_show_language0.2450.3910.7270.2741.0000.9980.9980.9980.5390.9710.9700.3110.4950.3310.5640.3090.3130.8970.8970.8970.4980.2760.1120.2310.1060.2890.2650.4370.158
_embedded_show_network_country_code0.5510.6000.7210.5320.9981.0001.0001.0000.5360.9310.9700.8430.5480.7310.9260.4990.5950.9900.9900.9900.6210.5040.0000.3850.3250.5140.5220.5871.000
_embedded_show_network_country_name0.5510.6000.7210.5320.9981.0001.0001.0000.5360.9310.9700.8430.5480.7310.9260.4990.5950.9900.9900.9900.6210.5040.0000.3850.3250.5140.5220.5871.000
_embedded_show_network_country_timezone0.5510.6000.7210.5320.9981.0001.0001.0000.5360.9310.9700.8430.5480.7310.9260.4990.5950.9900.9900.9900.6210.5040.0000.3850.3250.5140.5220.5871.000
_embedded_show_network_id-0.4410.157-0.7140.1380.5390.5360.5360.5361.0000.9710.9700.534-0.4590.6800.4960.388-0.4160.6610.6610.661-0.137-0.4350.1190.1250.1030.573-0.406-0.2891.000
_embedded_show_network_name0.7890.9070.9860.8390.9710.9310.9310.9310.9711.0000.9970.9610.7590.9070.9570.8110.8630.9800.9800.9800.9630.8510.1040.7560.6620.3770.8060.9571.000
_embedded_show_network_officialSite0.9500.8571.0000.8960.9700.9700.9700.9700.9700.9971.0000.9640.8240.9260.9640.8230.9730.9690.9690.9690.9910.8810.0000.8020.6780.3820.9500.9501.000
_embedded_show_rating_average0.081-0.173-0.262-0.1850.3110.8430.8430.8430.5340.9610.9641.0000.0070.3470.3690.3220.1770.3170.3170.317-0.0670.0980.338-0.2450.0050.3990.1020.1520.000
_embedded_show_runtime0.990-0.2310.1230.2890.4950.5480.5480.548-0.4590.7590.8240.0071.0000.6180.2620.3570.0510.4320.4320.4320.390-0.0980.0730.313-0.1150.4980.9850.5510.000
_embedded_show_schedule_time0.4830.5230.4850.4170.3310.7310.7310.7310.6800.9070.9260.3470.6181.0000.4250.3440.3010.4170.4170.4170.4270.3300.0840.2510.5060.2850.4250.4970.000
_embedded_show_status0.2140.3540.6540.2880.5640.9260.9260.9260.4960.9570.9640.3690.2620.4251.0000.5320.4040.6450.6450.6450.4430.2840.1620.2080.0920.3050.2240.4110.027
_embedded_show_type0.2840.2510.5970.2280.3090.4990.4990.4990.3880.8110.8230.3220.3570.3440.5321.0000.2190.4110.4110.4110.3170.1930.1100.4010.1010.1770.2970.8300.083
_embedded_show_updated0.125-0.402-0.220-0.1550.3130.5950.5950.595-0.4160.8630.9730.1770.0510.3010.4040.2191.0000.3340.3340.3340.0660.2790.1790.2960.026-0.0540.0880.4960.000
_embedded_show_webChannel_country_code0.3470.3000.7580.3440.8970.9900.9900.9900.6610.9800.9690.3170.4320.4170.6450.4110.3341.0001.0001.0000.6190.2850.1350.3060.1200.4500.3100.7200.121
_embedded_show_webChannel_country_name0.3470.3000.7580.3440.8970.9900.9900.9900.6610.9800.9690.3170.4320.4170.6450.4110.3341.0001.0001.0000.6190.2850.1350.3060.1200.4500.3100.7200.121
_embedded_show_webChannel_country_timezone0.3470.3000.7580.3440.8970.9900.9900.9900.6610.9800.9690.3170.4320.4170.6450.4110.3341.0001.0001.0000.6190.2850.1350.3060.1200.4500.3100.7200.121
_embedded_show_webChannel_id0.2620.0050.2210.2310.4980.6210.6210.621-0.1370.9630.991-0.0670.3900.4270.4430.3170.0660.6190.6190.6191.000-0.2500.1300.1640.0310.0780.2380.2280.058
_embedded_show_weight0.105-0.590-0.013-0.7080.2760.5040.5040.504-0.4350.8510.8810.098-0.0980.3300.2840.1930.2790.2850.2850.285-0.2501.0000.111-0.384-0.116-0.0610.0930.2120.061
airdate0.0690.0770.2820.0910.1120.0000.0000.0000.1190.1040.0000.3380.0730.0840.1620.1100.1790.1350.1350.1350.1300.1111.0000.1800.0000.3320.0550.0900.062
id0.0140.156-0.1400.4500.2310.3850.3850.3850.1250.7560.802-0.2450.3130.2510.2080.4010.2960.3060.3060.3060.164-0.3840.1801.0000.0630.0240.0070.2270.216
number-0.184-0.001-0.1260.0670.1060.3250.3250.3250.1030.6620.6780.005-0.1150.5060.0920.1010.0260.1200.1200.1200.031-0.1160.0000.0631.000-0.021-0.170-0.0951.000
rating_average0.3390.002-0.2090.1580.2890.5140.5140.5140.5730.3770.3820.3990.4980.2850.3050.177-0.0540.4500.4500.4500.078-0.0610.3320.024-0.0211.0000.293-0.1050.000
runtime0.971-0.1730.531-0.0030.2650.5220.5220.522-0.4060.8060.9500.1020.9850.4250.2240.2970.0880.3100.3100.3100.2380.0930.0550.007-0.1700.2931.0000.3540.076
season0.391-0.791-0.389-0.3500.4370.5870.5870.587-0.2890.9570.9500.1520.5510.4970.4110.8300.4960.7200.7200.7200.2280.2120.0900.227-0.095-0.1050.3541.0000.000
type0.0000.0880.0000.0560.1581.0001.0001.0001.0001.0001.0000.0000.0000.0000.0270.0830.0000.1210.1210.1210.0580.0610.0620.2161.0000.0000.0760.0001.000

Missing values

2024-10-29T14:34:40.473498image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-10-29T14:34:40.887704image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating_average_links_self_href_links_show_href_links_show_name_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_schedule_time_embedded_show_schedule_days_embedded_show_rating_average_embedded_show_weight_embedded_show_network_embedded_show_webChannel_id_embedded_show_webChannel_name_embedded_show_webChannel_country_name_embedded_show_webChannel_country_code_embedded_show_webChannel_country_timezone_embedded_show_webChannel_officialSite_embedded_show_dvdCountry_embedded_show_externals_tvrage_embedded_show_externals_thetvdb_embedded_show_externals_imdb_embedded_show_image_medium_embedded_show_image_original_embedded_show_summary_embedded_show_updated_embedded_show__links_self_href_embedded_show__links_previousepisode_href_embedded_show__links_previousepisode_name_embedded_show_image_embedded_show__links_nextepisode_href_embedded_show__links_nextepisode_nameimage_mediumimage_original_embedded_show_network_id_embedded_show_network_name_embedded_show_network_country_name_embedded_show_network_country_code_embedded_show_network_country_timezone_embedded_show_network_officialSite_embedded_show_webChannel_embedded_show_webChannel_country_embedded_show_dvdCountry_name_embedded_show_dvdCountry_code_embedded_show_dvdCountry_timezone
02730586https://www.tvmaze.com/episodes/2730586/neznost-2x01-seria-1Серия 121.0regular2024-01-012024-01-01T00:00:00+00:0023.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2730586https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedRussian[Drama, Comedy, Romance]EndedNaN19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost[]NaN10NaN337.0ИвиRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/282/707449.jpghttps://static.tvmaze.com/uploads/images/original_untouched/282/707449.jpgNone1704215354https://api.tvmaze.com/shows/51908https://api.tvmaze.com/episodes/2730595Серия 10NaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
12730587https://www.tvmaze.com/episodes/2730587/neznost-2x02-seria-2Серия 222.0regular2024-01-012024-01-01T00:00:00+00:0020.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2730587https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedRussian[Drama, Comedy, Romance]EndedNaN19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost[]NaN10NaN337.0ИвиRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/282/707449.jpghttps://static.tvmaze.com/uploads/images/original_untouched/282/707449.jpgNone1704215354https://api.tvmaze.com/shows/51908https://api.tvmaze.com/episodes/2730595Серия 10NaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
22730588https://www.tvmaze.com/episodes/2730588/neznost-2x03-seria-3Серия 323.0regular2024-01-012024-01-01T00:00:00+00:0019.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2730588https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedRussian[Drama, Comedy, Romance]EndedNaN19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost[]NaN10NaN337.0ИвиRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/282/707449.jpghttps://static.tvmaze.com/uploads/images/original_untouched/282/707449.jpgNone1704215354https://api.tvmaze.com/shows/51908https://api.tvmaze.com/episodes/2730595Серия 10NaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
32730589https://www.tvmaze.com/episodes/2730589/neznost-2x04-seria-4Серия 424.0regular2024-01-012024-01-01T00:00:00+00:0021.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2730589https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedRussian[Drama, Comedy, Romance]EndedNaN19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost[]NaN10NaN337.0ИвиRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/282/707449.jpghttps://static.tvmaze.com/uploads/images/original_untouched/282/707449.jpgNone1704215354https://api.tvmaze.com/shows/51908https://api.tvmaze.com/episodes/2730595Серия 10NaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
42730590https://www.tvmaze.com/episodes/2730590/neznost-2x05-seria-5Серия 525.0regular2024-01-012024-01-01T00:00:00+00:0020.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2730590https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedRussian[Drama, Comedy, Romance]EndedNaN19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost[]NaN10NaN337.0ИвиRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/282/707449.jpghttps://static.tvmaze.com/uploads/images/original_untouched/282/707449.jpgNone1704215354https://api.tvmaze.com/shows/51908https://api.tvmaze.com/episodes/2730595Серия 10NaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
52730591https://www.tvmaze.com/episodes/2730591/neznost-2x06-seria-6Серия 626.0regular2024-01-012024-01-01T00:00:00+00:0020.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2730591https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedRussian[Drama, Comedy, Romance]EndedNaN19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost[]NaN10NaN337.0ИвиRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/282/707449.jpghttps://static.tvmaze.com/uploads/images/original_untouched/282/707449.jpgNone1704215354https://api.tvmaze.com/shows/51908https://api.tvmaze.com/episodes/2730595Серия 10NaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
62730592https://www.tvmaze.com/episodes/2730592/neznost-2x07-seria-7Серия 727.0regular2024-01-012024-01-01T00:00:00+00:0020.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2730592https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedRussian[Drama, Comedy, Romance]EndedNaN19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost[]NaN10NaN337.0ИвиRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/282/707449.jpghttps://static.tvmaze.com/uploads/images/original_untouched/282/707449.jpgNone1704215354https://api.tvmaze.com/shows/51908https://api.tvmaze.com/episodes/2730595Серия 10NaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
72730593https://www.tvmaze.com/episodes/2730593/neznost-2x08-seria-8Серия 828.0regular2024-01-012024-01-01T00:00:00+00:0019.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2730593https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedRussian[Drama, Comedy, Romance]EndedNaN19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost[]NaN10NaN337.0ИвиRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/282/707449.jpghttps://static.tvmaze.com/uploads/images/original_untouched/282/707449.jpgNone1704215354https://api.tvmaze.com/shows/51908https://api.tvmaze.com/episodes/2730595Серия 10NaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
82730594https://www.tvmaze.com/episodes/2730594/neznost-2x09-seria-9Серия 929.0regular2024-01-012024-01-01T00:00:00+00:0018.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2730594https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedRussian[Drama, Comedy, Romance]EndedNaN19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost[]NaN10NaN337.0ИвиRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/282/707449.jpghttps://static.tvmaze.com/uploads/images/original_untouched/282/707449.jpgNone1704215354https://api.tvmaze.com/shows/51908https://api.tvmaze.com/episodes/2730595Серия 10NaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
92730595https://www.tvmaze.com/episodes/2730595/neznost-2x10-seria-10Серия 10210.0regular2024-01-012024-01-01T00:00:00+00:0019.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2730595https://api.tvmaze.com/shows/51908Нежность51908https://www.tvmaze.com/shows/51908/neznostНежностьScriptedRussian[Drama, Comedy, Romance]EndedNaN19.02020-11-122024-01-01https://www.ivi.ru/watch/nezhnost[]NaN10NaN337.0ИвиRussian FederationRUAsia/Kamchatkahttps://www.ivi.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/282/707449.jpghttps://static.tvmaze.com/uploads/images/original_untouched/282/707449.jpgNone1704215354https://api.tvmaze.com/shows/51908https://api.tvmaze.com/episodes/2730595Серия 10NaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating_average_links_self_href_links_show_href_links_show_name_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_schedule_time_embedded_show_schedule_days_embedded_show_rating_average_embedded_show_weight_embedded_show_network_embedded_show_webChannel_id_embedded_show_webChannel_name_embedded_show_webChannel_country_name_embedded_show_webChannel_country_code_embedded_show_webChannel_country_timezone_embedded_show_webChannel_officialSite_embedded_show_dvdCountry_embedded_show_externals_tvrage_embedded_show_externals_thetvdb_embedded_show_externals_imdb_embedded_show_image_medium_embedded_show_image_original_embedded_show_summary_embedded_show_updated_embedded_show__links_self_href_embedded_show__links_previousepisode_href_embedded_show__links_previousepisode_name_embedded_show_image_embedded_show__links_nextepisode_href_embedded_show__links_nextepisode_nameimage_mediumimage_original_embedded_show_network_id_embedded_show_network_name_embedded_show_network_country_name_embedded_show_network_country_code_embedded_show_network_country_timezone_embedded_show_network_officialSite_embedded_show_webChannel_embedded_show_webChannel_country_embedded_show_dvdCountry_name_embedded_show_dvdCountry_code_embedded_show_dvdCountry_timezone
47232920526https://www.tvmaze.com/episodes/2920526/dromkakar-utomlands-1x04-avsnitt-4Avsnitt 414.0regular2024-01-3100:002024-01-31T23:00:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2920526https://api.tvmaze.com/shows/73778Drömkåkar utomlands73778https://www.tvmaze.com/shows/73778/dromkakar-utomlandsDrömkåkar utomlandsRealitySwedish[]To Be DeterminedNaN45.02024-01-10Nonehttps://www.tv4play.se/program/9e5573b08abbda332d28/dromkakar-utomlands[Wednesday]NaN3NaN155.0TV4 PlaySwedenSEEurope/StockholmNoneNaNNaN444644.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/524/1310638.jpghttps://static.tvmaze.com/uploads/images/original_untouched/524/1310638.jpg<p>For two years, we get to follow Swedes who build and renovate the houses they dreamed of, abroad. But the journey to the dream home is not always straight.</p>1718874160https://api.tvmaze.com/shows/73778https://api.tvmaze.com/episodes/2920530Avsnitt 8NaNNoneNonehttps://static.tvmaze.com/uploads/images/medium_landscape/524/1310646.jpghttps://static.tvmaze.com/uploads/images/original_untouched/524/1310646.jpgNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
47242761042https://www.tvmaze.com/episodes/2761042/dimension-20-21x04-under-pressureUnder Pressure214.0regular2024-01-3119:002024-02-01T00:00:00+00:00NaNNaN<p>The Bad Kids realize how much work they'll be balancing this year. Adaine gets a job.</p>NaNhttps://api.tvmaze.com/episodes/2761042https://api.tvmaze.com/shows/56531Dimension 2056531https://www.tvmaze.com/shows/56531/dimension-20Dimension 20Game ShowEnglish[Comedy, Adventure, Fantasy]RunningNaN107.02018-09-12Nonehttps://www.dropout.tv/dimension-2019:00[Wednesday]NaN83NaN311.0DropoutUnited StatesUSAmerica/New_YorkNoneNaNNaN354216.0tt9646546https://static.tvmaze.com/uploads/images/medium_portrait/342/856895.jpghttps://static.tvmaze.com/uploads/images/original_untouched/342/856895.jpg<p>Heed the call of adventure and enter <b>Dimension 20</b> where Game Master Brennan Lee Mulligan, joined by comedians and pro gamers, blends comedy with tabletop RPGs.</p>1729775734https://api.tvmaze.com/shows/56531https://api.tvmaze.com/episodes/3034896K's AnatomyNaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
47252794533https://www.tvmaze.com/episodes/2794533/the-daily-report-with-john-dickerson-2024-01-31-episode-18Episode 18202418.0regular2024-01-3119:002024-02-01T00:00:00+00:0060.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2794533https://api.tvmaze.com/shows/75261The Daily Report with John Dickerson75261https://www.tvmaze.com/shows/75261/the-daily-report-with-john-dickersonThe Daily Report with John DickersonNewsNone[]Running60.060.02022-09-06Nonehttps://www.cbsnews.com/prime-time-with-john-dickerson/18:00[Monday, Tuesday, Wednesday, Thursday]NaN8NaN607.0CBS NewsUnited StatesUSAmerica/New_YorkNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/513/1283637.jpghttps://static.tvmaze.com/uploads/images/original_untouched/513/1283637.jpg<p>John Dickerson provides in-depth reporting on news stories and interviews newsmakers.</p>1722688947https://api.tvmaze.com/shows/75261https://api.tvmaze.com/episodes/2966145Episode 140NaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
47262833048https://www.tvmaze.com/episodes/2833048/abc-prime-with-linsey-davis-2024-01-31-episode-23Episode 23202423.0regular2024-01-3119:002024-02-01T00:00:00+00:0090.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2833048https://api.tvmaze.com/shows/76215ABC Prime with Linsey Davis76215https://www.tvmaze.com/shows/76215/abc-prime-with-linsey-davisABC Prime with Linsey DavisNewsEnglish[]RunningNaN90.02020-02-17Nonehttps://abcnews.go.com/Live19:00[Monday, Tuesday, Wednesday, Thursday, Friday]NaN6NaN616.0ABC News LiveUnited StatesUSAmerica/New_Yorkhttps://abcnews.go.com/LiveNaNNaNNaNtt27654411https://static.tvmaze.com/uploads/images/medium_portrait/514/1286702.jpghttps://static.tvmaze.com/uploads/images/original_untouched/514/1286702.jpg<p>Providing prime-time context and analysis of the day's top stories, as well as in-depth reporting and storytelling from around the country and the globe.</p>1728235929https://api.tvmaze.com/shows/76215https://api.tvmaze.com/episodes/3013782Episode 195NaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
47272750457https://www.tvmaze.com/episodes/2750457/camilla-hamids-bakresa-marocko-1x02-avsnitt-2Avsnitt 212.0regular2024-01-3102:002024-02-01T01:00:00+00:00NaNNaNNoneNaNhttps://api.tvmaze.com/episodes/2750457https://api.tvmaze.com/shows/73963Camilla Hamids bakresa: Marocko73963https://www.tvmaze.com/shows/73963/camilla-hamids-bakresa-marockoCamilla Hamids bakresa: MarockoRealitySwedish[]RunningNaNNaN2024-01-24Nonehttps://www.svtplay.se/camilla-hamids-bakresa-marocko02:00[Wednesday]NaN6NaN190.0SVT PlaySwedenSEEurope/Stockholmhttps://www.svtplay.se/NaNNaN443689.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/501/1253130.jpghttps://static.tvmaze.com/uploads/images/original_untouched/501/1253130.jpg<p>Come along to Camilla's Moroccan family where she gets to learn about the Moroccan baking culture together to understand more about where she belongs. Camilla has always felt too Swedish in Morocco and too Moroccan in Sweden and never really felt 100% at home anywhere. With this program, she hopes not only to offer new exciting baking pleasure, but also understanding and recognition.</p>1706117901https://api.tvmaze.com/shows/73963https://api.tvmaze.com/episodes/2750460Avsnitt 5NaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
47282941639https://www.tvmaze.com/episodes/2941639/trafficked-with-mariana-van-zeller-4x03-body-partsBody Parts43.0regular2024-01-3121:002024-02-01T02:00:00+00:0060.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2941639https://api.tvmaze.com/shows/49496Trafficked with Mariana van Zeller49496https://www.tvmaze.com/shows/49496/trafficked-with-mariana-van-zellerTrafficked with Mariana van ZellerDocumentaryEnglish[Crime]To Be Determined60.062.02020-12-02Nonehttps://www.nationalgeographic.com/tv/shows/trafficked-with-mariana-van-zeller21:00[Wednesday]7.879NaN2.0HuluUnited StatesUSAmerica/New_Yorkhttps://www.hulu.com/NaNNaN390354.0tt10370750https://static.tvmaze.com/uploads/images/medium_portrait/442/1106428.jpghttps://static.tvmaze.com/uploads/images/original_untouched/442/1106428.jpg<p>Armed with National Geographic's trademark inside access, <b>Trafficked with Mariana van Zeller</b> takes viewers on a journey inside the most dangerous black markets on the planet. Each investigation in the eight-part series embeds with Peabody and duPont Award-winning journalist Mariana van Zeller as she explores the complex and often violent inner workings of a smuggling network. While she dives deeper and deeper into these underworlds, Mariana reveals - with characteristic boldness and empathy - that the people operating these trafficking rings are often a lot more like us than we realize.</p>1720942651https://api.tvmaze.com/shows/49496https://api.tvmaze.com/episodes/2941650Caught in an African CoupNaNNoneNoneNoneNone42.0National GeographicUnited StatesUSAmerica/New_Yorkhttps://www.nationalgeographic.com/tv/NaNNaNNoneNoneNone
47292732350https://www.tvmaze.com/episodes/2732350/alle-elsker-david-5x15-viva-barcelona¡Viva Barcelona!515.0regular2024-01-3103:002024-02-01T02:00:00+00:0021.0NaN<p>The gang is in Barcelona and going to see Ingrid play a match. Andrea confronts her father about his future plans with Louise.</p>NaNhttps://api.tvmaze.com/episodes/2732350https://api.tvmaze.com/shows/54476Alle Elsker David54476https://www.tvmaze.com/shows/54476/alle-elsker-davidAlle Elsker DavidRealityNorwegian[]To Be DeterminedNaN22.02021-03-08Nonehttps://play.tv2.no/programmer/underholdning/alle-elsker-david03:00[Monday, Tuesday, Wednesday]NaN11NaN327.0TV 2 PlayNorwayNOEurope/OsloNoneNaNNaN399541.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/517/1293690.jpghttps://static.tvmaze.com/uploads/images/original_untouched/517/1293690.jpg<p>We follow manager David Eriksen and his charming but untraditional family. In David's new company, the pace is high and the drop is great.</p>1714772507https://api.tvmaze.com/shows/54476https://api.tvmaze.com/episodes/2732353Sykemelding og flyttemeldingNaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
47302765084https://www.tvmaze.com/episodes/2765084/disasterinas-my-drag-is-valid-1x15-luka-ghostLuka Ghost115.0regular2024-01-3100:002024-02-01T04:00:00+00:00NaNNaNNoneNaNhttps://api.tvmaze.com/episodes/2765084https://api.tvmaze.com/shows/73167Disasterina's My Drag Is Valid73167https://www.tvmaze.com/shows/73167/disasterinas-my-drag-is-validDisasterina's My Drag Is ValidTalk ShowEnglish[]RunningNaN24.02023-10-25Nonehttps://www.outtvgo.com/details/TV_SHOW/collection/6339796989112/disasterinas-my-drag-is-valid00:00[]NaN6NaN395.0OUTtvGoCanadaCAAmerica/HalifaxNoneNaNNaN441783.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/490/1226551.jpghttps://static.tvmaze.com/uploads/images/original_untouched/490/1226551.jpg<p>Disasterina, star of Sado Psychiatrist and The Boulet Brothers' Dragula, interviews a variety of drag artists to showcase the different styles of drag in performance, looks, and personalities. From seasoned underground fan favorites to the lesser known newbies, Disasterina and her talented guests prove that ALL drag is valid.</p>1728971819https://api.tvmaze.com/shows/73167https://api.tvmaze.com/episodes/3029154Gothess JasminNaNNoneNoneNoneNoneNaNNoneNoneNoneNoneNoneNaNNaNNoneNoneNone
47312848032https://www.tvmaze.com/episodes/2848032/fox-news-night-2024-01-31-episode-22Episode 22202422.0regular2024-01-3123:002024-02-01T04:00:00+00:0060.0NaNNoneNaNhttps://api.tvmaze.com/episodes/2848032https://api.tvmaze.com/shows/76581Fox News @ Night76581https://www.tvmaze.com/shows/76581/fox-news-nightFox News @ NightNewsEnglish[]Running60.060.02017-10-30Nonehttps://www.foxnews.com/shows/fox-news-night23:00[Monday, Tuesday, Wednesday, Thursday, Friday]NaN8NaN509.0Fox NationUnited StatesUSAmerica/New_YorkNoneNaNNaNNaNtt31100490https://static.tvmaze.com/uploads/images/medium_portrait/517/1293625.jpghttps://static.tvmaze.com/uploads/images/original_untouched/517/1293625.jpg<p><b>Fox News @ Night</b> is a live hour of hard news and analysis of the most compelling stories from Washington and across the country.</p>1716912888https://api.tvmaze.com/shows/76581https://api.tvmaze.com/episodes/2889864Episode 132NaNNoneNoneNoneNone185.0Fox News ChannelUnited StatesUSAmerica/New_Yorkhttps://www.foxnews.com/NaNNaNNoneNoneNone
47322751926https://www.tvmaze.com/episodes/2751926/the-tonight-show-starring-jimmy-fallon-2024-01-31-arnold-schwarzenegger-kathryn-newton-the-lemon-twigsArnold Schwarzenegger, Kathryn Newton, The Lemon Twigs202417.0regular2024-01-3123:352024-02-01T04:35:00+00:0060.0NaN<p>Actor Arnold Schwarzenegger; actress Kathryn Newton; The Lemon Twigs perform.</p>NaNhttps://api.tvmaze.com/episodes/2751926https://api.tvmaze.com/shows/718The Tonight Show Starring Jimmy Fallon718https://www.tvmaze.com/shows/718/the-tonight-show-starring-jimmy-fallonThe Tonight Show Starring Jimmy FallonTalk ShowEnglish[Comedy]Running60.060.02014-02-17Nonehttp://www.nbc.com/the-tonight-show23:35[Monday, Tuesday, Wednesday, Thursday]4.498NaN347.0PeacockUnited StatesUSAmerica/New_Yorkhttps://www.peacocktv.com/NaN35853.0270261.0tt3444938https://static.tvmaze.com/uploads/images/medium_portrait/534/1335993.jpghttps://static.tvmaze.com/uploads/images/original_untouched/534/1335993.jpg<p>Emmy Award and Grammy Award winner Jimmy Fallon brought NBC's "The Tonight Show" back to its New York origins when he launched <b>The Tonight Show Starring Jimmy Fallon </b>from Rockefeller Center. Fallon puts his own stamp on the storied NBC late-night franchise with his unique comedic wit, on-point pop culture awareness, welcoming style and impeccable taste in music with the award-winning house band, The Roots.</p>1730212150https://api.tvmaze.com/shows/718https://api.tvmaze.com/episodes/3034111Reba McEntire, Lauren Lapkus, A.J. & Big Justice, The Rizzler, Sevdaliza, YseultNaNhttps://api.tvmaze.com/episodes/3034921Olivia Rodrigo, Keri Russell, Andrea Bocelli, Lauren Daiglehttps://static.tvmaze.com/uploads/images/medium_landscape/502/1255817.jpghttps://static.tvmaze.com/uploads/images/original_untouched/502/1255817.jpg1.0NBCUnited StatesUSAmerica/New_Yorkhttps://www.nbc.com/NaNNaNNoneNoneNone